How To Stand Out From the Crowd

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Hello, everyone. Welcome to today's live stream. How to stand out from the crowd. My name is Ryan and I work here at Data Camp on the marketing team. Today's presentation will be given by Jen Bricker, who leads the Career Scientists or career Services team, mentoring learners during their job search here at Data Camp. The presentation will also be followed by a Q and A, so make sure you ask questions in the comments section as the talk goes along. So without further ado, Jen, take it away.

Jen Bricker. I'm the head of Career services here at Data Camp. I've been with datacamp for about three years, first on the content team, helping to build courses, hire instructors, and really building my connections within the data science community. Now, on our new certification and career services side, I work with our certified users to help them prepare their resumes and their personal brand and help them while they're applying for jobs. So what I want to do today is go through a few of these points with you. We'll cover some tips for resumes and portfolios. We'll probably spend most of our time there, talk a bit about COVID letters and then some cool tools for job searching that kind of mesh in with your personal brand. Please bring the questions on. I've left plenty of room for any questions you might have at the end. I won't be answering them during the presentation, so please write them in and Ryan will make sure I have them available at the end of things. So to get started, I just wanted to run a little scenario by you and see if this, if you fit this scenario or have experienced it, you hear or have heard that there's a huge shortage of data scientists in the marketplace. This little chart kind of shows the data fluency in the world at large, where there's a whole lot of people who know nothing about working with data. There's some people who are familiar with data and yet the demand in the market is way higher. And then there's those, like many of you, who are probably at the junior data analyst or data scientist level, still having a huge gap between what the market needs and what the available staffing has. And then the expert data scientists still have this career gap. And you're like, this is fantastic. I love working with data. I want to fill this gap. I want to get a job as a data scientist. So you invest in yourself, you learn data science on platforms like Data Camp, you go ahead and you get certified so that you've been tested on the various aspects of data science and, and then you start applying for data Scientist jobs. Then all of a sudden you realize nothing happens. You're like, oh my gosh, why am I just applying and applying and applying and I'm not hearing anything back. What I hope to do after today is get it to this where you just don't know which job to take, that you have too many offers and too many interviews to juggle. And we're going to do that by focusing on your personal brand. So the keystone to your personal brand is going to be your resume and your portfolio. This is really the way to set a good first impression with folks. So resumes are really informative and they're helpful. But the important thing with resumes is you need to keep it simple. You have to keep in mind that oftentimes the first thing to review your resume is actually computer. Applicant tracking systems are used by most companies and therefore what that tracking system is doing is literally scanning your resume for keywords and phrases. And those keywords and phrases they're looking for are coming from the job post that was listed. If by some chance it's a human screener in the people ops or human resources team that's looking at it, and they also have the sort of key skills that they're looking for that the hiring manager gave to them. If you want to prepare your resume the right way, you want to make sure there's no header sections, no charts, no background art or images. It may look pretty artistically and from like a user experience. It might feel good to have a very artistic looking resume. The problem is machines don't really recognize that and they have a hard time extracting words from text boxes. So a very simple formatted resume will get you a lot further because then the applicant tracking system can really easily pick out what your key skills and experience are. Another important thing is you don't need to put everything and the kitchen sink on your resume. Try to limit it to one page. If you have, let's say, more than five years of working experience, you might be able to make it two pages. But if you're straight out of school or have very little professional experience, there's no reason whatsoever to have a resume longer than one page. Similar to my first point, keeping the font simple is going to be really important. You don't need to stand out in the crowd because most likely the thing that's looking at your resume is not human, it's a computer. So they don't care what style font you're using. And you want to make sure that it can pick up all of the relevant experience that you have. The other thing is it just looks really clunky if you have lengthy URLs to your website or blog, to your LinkedIn profile, to your projects in GitHub or wherever you have them stored. Try to use hyperlinks whenever possible. At the point that someone's going to be interested in going in greater detail, it will be a human and they just want to look at a hyperlink. They don't care what the web address is for or where your information is stored. And then if you're well experienced professionally and you've been working and doing this for a long time, you really don't need to include more than 10 or 15 years of experience. So this may not apply to you. But just keep it in mind that the first job you had out of college is probably not super relevant to the job you are going to have in 10 or 15 years. So you want to make sure that your professional experience you have listed is really relevant to what you're applying for. I just wanted to show you an example. So this is a pseudo real resume that I received. I changed the name and contact info, but everything else is quite true and honest. This is an original resume that I received. As you see here. You would think this person really has it together. They have tons of experience. On first glance you're like, where do I look? You're like, this looks pretty nice. The problem is they spend almost an entire page talking about training and only a small portion of the second page talking about their professional experience. So this isn't really necessarily showing them off in the best light. So when I'm working with this candidate, we actually got it down to this. It's a much more concise resume. It has all the same information but in a highlighted form. And it's much simpler if it goes through an applicant tracking system for it to pick up all of the keywords that this person brings with them. So I just wanted to show you it's totally possible to take something that you might have as two or three pages and really consolidate it into a resume. I will say I'm going to talk a lot about resumes. I'm not necessarily going to talk about CVs. Perfect much. They're similar but different because in CVS they often are much longer and have more extended detail. And I'm also not really addressing what academia looks like for resumes because they there's a different standard involved when you're talking about publications and what you've had to get tenured in previous roles. So I'm really just focusing for people who are intending to apply for data scientist roles here and as resume style instead of a CV style information. So the other key point with resumes is you want to make sure you're talking about why you're best for that specific role. This sounds exhausting, but it really makes a big difference if you customize your resume for every single job you apply for. I'm just going to say keywords over and over again throughout today. Have patience because they're so important using keywords and phrases. If you're looking at applying for a job, take that job description that you've been given and literally go through and highlight the keywords for skills and technologies that they're looking for and see how that relates to your resume and, and what can you do in your resume to make sure it reflects in the same language the type of work that you've done that they want you to be doing. In a lot of ways, people take the summary section at the top and they make these into little mini bios of what you're interested in in achieving in a new role. That's not what a company wants to see. A company wants to see why are you best focused for that specific role. So you need to tell them in three sentences or less why they should look further into your background and talk to you about this position. You really want to bridge that gap for them. It's not of interest to know that you're hoping to get started in data science after you've learned all of these great skills and that it's your dream job that doesn't tell them anything valuable to them. But if they know that you've applied these machine learning models in a successful way and is on a successful project, even if it was a personal project or a Kaggle competition or a school project, that, if it relates to the job as it's been described, will get you so much more attention and will make it easy for them to understand why they should talk to you more about the position. You also have to understand the first people looking at your resume. If it's a human looking at it, is likely not a data scientist. Very rarely are the first screeners going to be the hiring manager. More often than not, it's someone on the people ops. A recruiter could be an external recruiter or a technical recruiter. They may or may not have any understanding about data science. So you need to bridge that gap for them. And you don't have to explain the data science skills, but you have to address the skills that are being highlighted in the job description, I put here a sample of a really good summary statement. It's been modified a little bit just to make sure the person stays anonymous, but highly motivated. Insightful data scientists with a master degree in applied stats with three plus years of analytics experience in the airline industry. Eager to support the B2B demand gen team at Acmeco with top notch skills in sales and marketing, data analysis, creative problem solving, machine learning in previous positions supported a 15% growth in quarterly membership enrollment. Doesn't that sound like someone who you want to know more about and really try to find out are they going to be a good fit for your B2B team? Possibly. Lastly, I really want to highlight this. This is a good first impression. When you're describing your professional experience and the work that you've done, you don't want it to sound like a job description. You actually want to show what you achieved while you're in that job. So there's a thing called PAR statements. PAR stands for P for problem, A for action, are for results, and it's a way that you can show what problems you took action on and made an impact on your team. You don't have to list every single task you did in a job, but if you can put a couple of really high quality PAR statements, it'll get a little bit more attention and people will see how you are engaged in your team, your team's goals, and how you've contributed. So here's just a quick example of a PAR statement. So the problem the first three parts are sort of the workbook style. The problem is after years of wear and tear and numerous updates and fixes, a tool used to report and fix bugs had become unwieldy. It was integral part of the software process and its malfunctioning had cost the company thousands in losses. The action that this person took was utilizing appropriate data re engineering tools. I analyzed and restructured the entire system within six months and then the result from this is a smooth and fast operation of the tool. This resulted in a 20% reduction in time spent and increased productivity by 35%. Now this is obviously a little bit fictitious, but I just want to give you an example. So those are all the three aspects. If you wrote all of this in your resume, there's no way you could have a one page resume. So if we put this all together in a concise way, we can say restructured and outdated and unwieldy Bug fixing tool critical to the software process within six months, hence reducing the time spent working with the tool by 20% and increasing productivity by 35%. So in one sentence, we've really captured all of the work that went into it, and it sounds a lot more meaningful than maintain systems, which I would hope you wouldn't write in that way. But in general that's often what people write like. I was responsible for maintaining our bug tracking systems. That doesn't really tell you anything whatsoever about the work that you've accomplished. Moving on to portfolios, you guys may want to talk about this for the whole hour. We're actually not going to spend a whole lot of time on it, but there are some key points to keep in mind. With portfolios, it is good to have a centralized repository, whether it's a personal website or a blog, whether you share your GitHub with links to your various projects, there's lots of different forums that you can use as a central repository. Even here at datacamp we have our Workspaces tool, which is where you can actually be bringing in your notebooks and publishing your notebooks so that you have that as an additional resource. If you're not super comfortable in GitHub, the really key thing to your portfolio is making sure that you're using original data sets and original projects. You want to make it interesting for someone who's reviewing your portfolio because they probably have seen hundreds if not thousands of projects in the past. You can think of all of the common data sets that you find on Kaggle or some of the other competition sites or open data sources. It's probably really boring for them to see yet one more analysis of the same thing. Pick something that's personal to you, that's interesting to you, and do a project around that. So find data that you actually are keen on. Make sure the code you're using is original code. Just copying code from another source. It will be easy to recognize and not really worth a whole lot. But if you're putting some investment into a project that means something to you that's original, without the commonality of overused data sets, you're much more likely to get a positive response. It's really interesting. One of the best projects that someone shared with me was a machine learning model to tell you how long it would take you to learn to play particular music types. Now, this doesn't sound like this great revolutionary business thing, but this person invested a lot to study their own habits in learning to play the piano, the type of music that they were playing, and the length of time say they used that as the test set. And then they created a model for other people to test out to see if they wanted to learn this level of complicated music, how long it would take them to learn the piano to get to that point. Pretty interesting, very unique. And I can tell you the hiring manager in that situation definitely took a second look at this individual because it was a real standout type project. Your portfolio, while it's important, is not the first thing people are looking at. Just to remind you, the first people who are screening your application when you apply for a job is either an automated applicant tracking system or it's a human, like an HR screener who's not a data scientist. So make sure while you're spending time developing a portfolio, you really have to fix the other pieces as well, because the projects are are only going to get looked at if you make it past the second or third round. That's when the hiring manager is going to get more involved in the process. And that's when they're going to take a second look and really see what's the quality of your work before they have a chance to do a technical test with you. So that's all I'm going to say right now on portfolios, but keep it in mind. Cover letters are another hotly debated topic. Cover letters are really essential, and maybe you're sensing a theme here, but it's going to be really important for you to customize your cover letters for every job that you apply. Just like with your summary statement how having a mini biography really doesn't tell the employer much of anything. The same goes with a cover letter. Having a generic cover letter won't get you anywhere. You can easily spot them. As a hiring manager, you want something that shows that employer you looked at the job, you looked at the company, and you are the best person for that role. And here's why. The other thing to keep in mind is keep it concise. If a human is reading a cover letter, they're really only going to take 30 seconds, maybe a minute to read it. So if you have it longer than that, it's just going to get glossed through and nothing's going to really stand out. So what should you have in your cover letter? I suggest you keep it to no more than three paragraphs and you're going to be like, whoa, how am I going to cover everything that's needed in these three paragraphs? So I've tried to highlight it for you here. So the first paragraph, this is if you got a referral for the job or you've networked with someone in that company who suggested you apply for that job, you want to make that the first statement. You really want to say I'm really happy to apply for this job based on conversations with so and so. They highly recommended I would be a good fit for this role. Something like that. So if you have that connection, flaunt it. It's important. It helps a lot in getting you past the first step. The paragraph should really respond to the job description as it's written. Again, you want to show why you're good for this job. So take those keywords and phrases from the job description in the post and draw parallels to the work that you've done, whether in school, in a professional setting, whatever the type of work is that you've done. Make sure they see how it's aligned with what they're looking for. So that's the first paragraph. Like hit them hard with all the relevant details because that's where they're going to spend the most time. If you, if you're lucky enough for them to get to the second paragraph. This is where you want to show that you've done your research on the company. Really think about taking the time to know who's in the company, what their focus is. If they're a startup, where they're at in their growth, like what are they putting out there publicly of their mission even if they're not a startup, if they're a bigger company, check the news, see what's been put out there of new opportunities, see if you can figure out where their growth area are, growth areas are, and really try to make a connection of like why is their mission or their values. How does that resonate with you? You can look at sources like Glassdoor or Angellist and you can really find some of the company background information in a static way. And then a good old Google search on the company can probably give you a little bit more about the news and media pieces. Most company websites have a media section, so see what they're sharing out there publicly as well. You can do some checks on social media, but you might as well get it straight from the source and go to their website and see what they're saying about themselves. The more you can show that you've actually looked at the company and they're not just another application you're hitting submit on, the more they're going to likely want to talk to you. The last paragraph is short and sweet. It's going to be the call to action of thanking them for their time and how you look forward to talking with them more. Let's assume that you're going to get that second call or that follow up call from them. So let's just put it, you know, set the tone in a really positive manner and with confidence. Close out the conversation short and sweet. That's your cover letter. The you guys might have some questions More about COVID letters There are probably bits and pieces you can keep as common threads, but really try to recreate them for each job. It might sound tedious, but it also means that you're putting a little bit more thought into every job you're applying instead of just hitting submit without a cover letter for any job. One thing to keep in mind, and I'll emphasize this a little bit later on as well, but when you're applying for jobs, think about applying directly through the company's website. It might be very tempting to apply directly from LinkedIn where they have the easy submit. Or it might be you're on Indeed.com and want to just hit submit and let them compile all your information and throw it out to the employer. It's a lot better if you do it yourself. It might take you a little bit longer because you'll have to customize your resume, you'll have to customize your cover letter. But as someone who's hired hundreds and hundreds of data scientists, I can absolutely assure you that things that are submitted through Indeed are really not highly valued. I'm sorry to Indeed for saying this in this public setting, but it's really hard to stand out from the crowd if you're literally just getting giving your generic resume to somebody. You really want to make that connection and the COVID letter is pretty essential for that. The last part here I want to talk about before we get to your questions is looking at some job searching tools and you might think you know the best tools out there and they could certainly be working really well for you. But I wanted to highlight a few features that maybe you haven't heard of yet or haven't tested out. So LinkedIn, you probably have heard of it. It's great. It's really a one stop shop for really anything job related. You can first of all customize your URL in LinkedIn so it's all about you and it's not some random list of numbers. I can show you how in a moment you can develop what is known as like a master resume. So on your shareable resume you're limiting it to one page, but you still have lots of great experience and volunteer work and skills that you want to share out. You can do that through a master resume. LinkedIn is a great way to do that because people often are looking at your LinkedIn to find out more about you. So this is where you can share the more, which is really cool. You can feature your projects. So let's say you don't have a GitHub yet, but you still want to share out some of the project work that you've done. You can actually do that on LinkedIn. You can have links to outside documents. You can do if you have a presentation style, you can share a PDF. If you've done published work, you can link to that. It's really cool to utilize that feature. Projects area. You can list your certification. Let's say you've gotten the Data Camp Professional Data Scientist certificate and you're like, I want to put this up on top and share it with the world. Great section to do that. If you've taken coursework, you can add that in as well. You can use LinkedIn for job searching, which most people know about but maybe haven't delved in. And we'll go into that in a minute. A little bit more of how you can really use the job searching a lot more effectively. And the last few areas here. Oh, networking. Obviously it's essential. You can do some of your company research here. You can find out if you have any connections within that company or even second or third connections, or you can just figure out who the right person is for you to reach out to. And it's a great way to do Networking. The last three things here are what are considered premium tools that LinkedIn offers. If you are actively looking for work and this is how you're investing your time right now, is to change your career, upgrade your career. I do recommend spending the money for a few months to get some of these premium services. They're really nice being able to communicate through InMail so you can directly communicate with someone even if they're not your connection. Very important. It's a nice way because finding someone's personal email or work email is sometimes really challenging to do. It's a great way to connect with them. There's a whole interview prep section where you can look at sample interview questions and it can be very general of like broad interview questions of why should you get this job? All the way to very specific role specific questions. So it's really cool to see that you can also under premium you can submit answers and, and get feedback about how you would answer that question. Super cool tip. And then the resume building, they actually have a resume building feature that will look at your content from your profile and set it up specifically for a job that you're interested in. So let me just show you a little bit. If you're looking in your profile, you probably have your home and your network. The third tab here is Jobs and it just pops up here. You can immediately jump into. This is not a live screenshot, it's just an image for now. But you can immediately put in the company, the skills, the job title you're looking for and the location you're looking for. And it looks like a very traditional job board. But if you go over into the More section, that's where you have the interview prep and the resume builder section. So for the interview prep, what it gives you, for anybody, it gives you the common, the most common questions. When you have a premium access, you can, like I said, cater it to your specific role you're applying for. So typical questions that get asked in a data science interview. And then you can also test out and practice your answers and get feedback on your answers. So pretty cool feature. It's definitely worth testing out if you're actively interviewing right now. The last thing is the resume builder. I put in my profile and I said I want a job as a data scientist. And what it does is keyword check, ding, ding, ding. It's a little ats, it's an applicant tracking system and it says, well, most data scientists roles are looking for these things, which ones are found in your resume? So these are all the ones found in my resume. And, and here are the things that I don't have, which is true. I do not have Python programming language. I'm. Yeah. Anyway, so it was pretty spot on. I felt comfortable with the response it gave me when I put in that I was looking for a data scientist role. You can look at all sorts of roles, there's not a preset list and you can see how does your resume relate to it. It will help you then give you the space to edit it and, and save it and you can customize it for particular roles. So even if you're applying through LinkedIn, you can still send some level of a customized resume to a company. So again, it is a premium feature and I am not paid by LinkedIn. I have no affiliation with LinkedIn, but I think it's a really smart investment. If you're struggling with this, if you're not working with a career coach, then it's nice to get this feedback elsewhere and this is an easy access way for everyone to get some feedback on their resume and what they have in LinkedIn. It also ensures that you're putting all the right things in LinkedIn and making sure you're representing yourself well in the LinkedIn community. Another sort of unknown or unutilized tool is Google, which you guys are probably all laughing at me of, like really Google for job searching. But it works. If you put in, in this case I just put data scientist, job and remote. It pops up its normal results as it normally does. But if you look, there should be a section that's in blue that says Jobs. And when you click on that, it pops you over to an actual job board. And it's pretty cool because it's scraping the data. I mean, as data enthusiasts, you're probably really into this like I am, but it's scraping the data from all these other sites. You can see all the different sites that the jobs are coming in from and you can explore the job the company. You can apply through the site that the job came from. It also gives you links to the company so you can apply directly with the company. If you wanted to filter a list, let's say, okay, these are all data scientists jobs in Toronto. But maybe I really want to focus more on data engineering. So you can go and click on the data engineering and it will give you the subset that's really has data engineering as part of its job description as well. It's a really cool tool. They don't have a landing page called Google Jobs. You have to literally use the normal search function and go into the job section. You should recognize it because it would have this blue header. I don't know why they don't have, I don't know anything about the back end of Google. I have no idea why it's not its own landing page, but. But it's a really valuable tool and it's a really cool way you can bookmark them. That could be your central sort of research for jobs. Again, I highly recommend you don't apply through these collated groups here. I highly recommend going straight to the company to apply, but you can at least get a sense of what the job's about and have some easy access to the links to the company, some of the company history and you can see sort of activity of how long jobs have been posted and things. That's really it because I wanted to give plenty of time for some questions. So I'll give you guys a minute or two here to ask your questions. Give me a second. To get a sip of water. Cool. I see some questions coming in. I'm actually going to stop sharing my screen and come on camera unless there's a reason to. Start sharing again. I will. Let's see here on the questions. So one of the questions Will the presentation be shared? Will we have access to the slides? Yes, the recording will be shared, so whatever site you're watching this on, the recording will be there. We'll make sure to also post the slide deck to datacamp's blog so that you have access to that if you want this information written out. I know I threw a ton of information out there to you, so it's often useful to have the materials to follow up with another question here. Is there access for getting career services through Data Camp to talk with me again or my team with the Career Services here in Data Camp? Access for one on one support is actually given to anyone who passes our certification process. So as I said, we have a professional Data scientist certification. Once you receive that certificate, you actually have free access to us and we'll support you and give you your customized feedback and help with your job search. We do have a Data Analyst certification coming up. I would say that will probably be ready by early fall, so keep a lookout to that if you're more on the analytics side versus the data science side. But absolutely our career services are all focused on certified users from datacamp. A little switch of topic, but I've heard that cover letters don't really matter. Is this true? And this is kind of a debated issue depending on sort of who you are in the hiring process realm. So cover letters do matter. It might not be the most important thing to certain parts of the interviewing process or squad, but it will make a very positive first impression if you have one. And it really gives you a free form for explaining yourself and giving your take on why you're best for the role. That doesn't really have much space in a resume to convince somebody, especially if you are doing a career transition. It's a perfect opportunity for you to explain what you did in the past, how you invested in learning data science, and how you're going to take that knowledge with your previous professional experience and apply it in the role you're applying for. So it's really essential. Not every hiring manager looks at cover letters. Most do. I think you have to err on the side that they want to know more about you, so it is worth the investment. You will start understanding the mechanics of building a good cover letter. It will get easier over time it might sound really tedious, but I'm asking you for two unique paragraphs. The third one you can kind of keep the same. Just make sure it's specific of what company you're applying for. But really customizing those two paragraphs, you'll get a feel for doing it more easily and it will make a difference for sure. Another thing is I already I use Data Camp for learning. Do I have access to career services or is it something that I have to buy separately from my datacamp subscription? As I mentioned, the career services is attached to the certification. But the good news is certification is free for all datacamp subscribers, so you have access to it. It is free. There's no additional costs involved with it. It's really cool if I don't say so myself. Switching areas Again, how many projects should I have in my portfolio? It's really not about the quantity of projects in your portfolio. It's really going to be about your quality and originality in that portfolio. That's going to make the much bigger difference than having 50 projects, which is excessive. No one should have 50 projects in their portfolio. If you have a wide array of projects, make sure that they're relevant to the work you're doing. So if you're applying for something in the finance world, make sure at least one of your projects has something to do with the finance world. Make sure you can relate the skills that you've applied to the project are skills that you're going to need in the job you're applying for. Or just make it so oddball interesting that they're going to love it regardless. But that person I told you about with the piano practice time model that they created, that was their portfolio. They didn't have 10 other projects. They put all of their emphasis on this and they really stood out from the crowd. Originality, as I said, plays a huge role when it comes to portfolio projects. A common question I get is should I include my photo on a resume? And this is where resume versus CV comes into play. So those of you who are watching this from Europe or other places outside the us, it's really common to have photos on it. If that's where you are, then you probably should keep having your photo on it. CVs, as I said, are a lot longer. Traditionally they're kind of a bit of a full list of all of your skills and experience. You can combine the two and have a one page resume with a photo on it, though even I think it's pretty common in today's world. So don't lose the tradition of the standard practices of where you are. In the US and most of North America, it's not very common to have a photo on a resume, so I would not include one. If you're applying to US companies in the US Or Canada, I would probably keep it off. A common question I get is this one of what do I say when I'm actually networking with someone? So you did all of your investigating on LinkedIn and you found a person that you really want to talk to, but you're like, how do I start a conversation with them? And I think you have to keep in mind you're not going to ask them for a job. That's not what networking is. Networking is trying to find out about the community, whether it's within the company, whether it's in the location that they are, whether it's someone with specific skill set that you're trying to be working with as well. And so it's really about what can they help you with, information wise. So you would want to try to reach out to them and express, you know, I saw that you work for ABC Company. I've been really interested in this industry, whatever it is, and I'm wondering if you could have a spare few moments to talk with me about your experience at the company and in this industry, whatever that might be. That's a really nice way. It's a specific ask of what you're wanting from them, but you're not asking them for a job, you're asking for their experience and their insight. Most people are really happy to foster and mentor someone and mentor them in their career. So I do highly recommend you try this out. It doesn't matter whether you've applied to a position at that company or not. The networking ideally would happen beforehand and you never know what will come up of it. They might know something that's happening behind the scenes, that's not public in terms of open positions in that company or, or they may know from their own networks of other people who might be looking for folks and might have an inside track. So keep an open mind. Is really intimidating to take that first step when networking, but I absolutely recommend you try it. There's some great tools out there on the web to help you craft your message, but it really should be about a specific ask to the individual. And it's not asking them for a job, it's asking them for insights about either the work they do, the company they work for, or the community that they're part of. So let me look at More questions here. What do you think a resume should have or has more importance? A well descriptive resume within two pages or a cut to the point resume? Everything cluttered into a page? Well, nothing should be cluttered into a page. So clutter is not a good look for a resume. It can be concise. And this is why you would want to be customizing resumes, particular jobs, because you can cut out roles that you've had or details about the roles that you've had if they're not relevant to the work you're applying for. So you can pick and choose what you highlight from each of your previous roles. I'm assuming the person who wrote this probably has a number of years of experience and they're trying to apply to either change their career or upgrade their career. And this is where it's going to be really important of what's the most valuable experience that you've had that relates to the particular job you're applying for. So definitely not cluttering it into one page, but limiting it to one page. Especially if you're like at that five year mark or so of professional experience, you should be able to get that into one page, but you're only highlighting the work that's most relevant to what you're applying for. Someone asks if there's any value to including previous work experience if it's in a different industry. And I would say absolutely. If you're trying to do a career switch and move into a new industry, there's still aspects of that work that are probably transferable to your new job. So you want to highlight those aspects. Are you a good team lead? Have you managed lots of people? Have you gone through relevant trainings? Have you used the skills that you expect you would use in the new job? Think about what is it? You normally don't cut yourself off completely and then start from scratch. There's usually aspects that you're going to carry through. Is it your project management ability? Is it? I already mentioned the people supervision ability. There are things that are absolutely transferable from job to job regardless of what industry you're in. So you want to think about it. You also don't want to present a resume with tons of gaps. So you would still want to have the position listed with the role, even if it's not super significant, especially if it takes up most of your recent past. So how many certifications are too many to list and which ones are the main ones? So I would think about it this way. There's classes, so if any of you are Data Campers and have taken courses or projects on datacamp probably have a ton of statements of accomplishment for every course that you've done or every project that you've done. Listing those, first of all, on your resume is probably really excessive. But in the case of Data Camp, we have a comprehensive certification that is all encompassing in the primary areas of data science. If you have that certification, then you're able to list that, and then maybe in the supporting description, you can say additional 50 hours of coursework leading up to the certification. You want to try to represent certifications that are broader, that really encompass the area as a whole and not necessarily a specific course about a specific technology. It can become redundant. In LinkedIn, you have the opportunity to list all the classes that you've taken. You probably want to distinguish your certifications from your education area so you can do it that way. So I hope that answers the question. If it doesn't, write it down, we'll go back to it. But there is such a thing as too many, because it looks like you're just trying to check boxes off. So really think about which ones are most relevant for what you're applying for. When applying to a remote job, is there something in particular to keep in mind? Well, this is a really interesting thing right now because we're in a very different world than we were a year and a half ago. Remote jobs right now are fairly common, but you have to keep in mind there is almost always in every job description that's out there, a little asterisk, a little note that says currently remote, expected to be back in office at a certain date and time, you still have to have some flexibility. And if you're applying to something that's currently remote, that may not stay remote forever. So keep that in mind. The other thing is, if you're applying to a remote job, but it's in another country, you still have to think about visa situation. And it's a very complicated situation to get work sponsorship for visas. So keep in mind that you might not get considered. So let's say you're applying for something that's listed as a remote job, but it's a US Company, but you're, let's say, based in France, and you're a French citizen, a EU citizen for that US Company. For you to be based in France means they still have to have the ability to hire you in France and you would be listed as a French employee. So one of two things have to happen. They have to sponsor you to get work permission for a US company, or they might have to hire you as a contractor, or they might have to have governmental approval to basically be a business in France, because by having an employee there they have to be incorporated there. I'm overly simplifying it. I am not in any means a lawyer dealing with immigration issues, but it's complicated. If you're in the country where the remote job is being posted, it's probably a lot simpler. But still, keep in mind there may be the expectation that you move to an office location if that's where they decide ultimately the workplace will be. I think a lot of companies are going through a dilemma right now of what does post Pandemic World look like. So just keep that in mind. So a question about Kaggle and Kaggle data sets. Is it necessary to get a high score in my submission to add it to a portfolio? I would say with Kaggle, if you're winning the competition or in the top 5%, that's great. And it's probably worth noting someplace, probably more on LinkedIn than in your portfolio. Kaggle data sets are the most used by all data scientists, especially learning in the learning phases of data science. So those are going to be the most commonly used data sets out there. What can you take from participating in that competition and apply it on a topic that is original and new and not already sort of worn out by by the Kaggle world. So keep that in mind. It's worth it's always worth noting. It's just a matter. Is it worth noting on your resume? Probably not. Is it worth noting in your portfolio? If you have a website, you could have a section devoted to your competition or hackathons that you've participated in in LinkedIn, you can certainly add that in as part of your featured projects. But how relevant is it going to be to the work you're applying for? So always keep that in mind. Is there free access for students? I'm assuming this means to just Data camp in general. Right now, the way Data camp for the classrooms work, there is access for students, but it has to come through the professors in the university or if you're in the US High school, students can also get free access through their teachers. So there's not at this point free access to individuals. I believe there are some special pricing for students, but if you're part of a university, you can have one of your professors request a data Camp for the classroom account and you can have a group account for the term. So highly recommend doing that. It's totally free for the professor and you do get full access, including certification and career services. What are some good things to look for when finding a career coach? I would say specialization helps a lot. You want to talk to if you're looking for a data science role, you want to make sure the career coach understands a little bit about data science positions. You don't necessarily and oftentimes data scientists get thrown into engineering as like they're one in the same and the hiring process is the same, but it's not true. There's actually just a difference between software engineers and data scientists and there should be a difference trying to find a career coach who has some specialization. A lot of companies that focus on data science, like datacamp and some other boot camps, they have career services associated with their product. Datacamp's unique in that it's totally free if you already have a regular subscription. So it's kind of nice. So you could start there to try to make some connections. But finding a career coach is really about how they're going to help you. They're not necessarily going to find a job for you, but they're going to really help you make the most powerful impact when applying. So they have to understand what the world of data science looks like right now. How should I apply if I want to apply for jobs but I need sponsorship? So this will be kind of the last thing I answer in terms of international job searching. It's complicated and I think in today's world it's going to be even more complicated. There's been a great reduction in the US of having certain types of visas approved because of the pandemic. And I'm sure the US is not the only company like this. So I think you have to broach it carefully. Certain companies are going to be much more able to do visa sponsorship. So larger companies that already have a multinational footprint are probably going to be much more likely to be able to hire internationally, whereas smaller companies, it's such a huge process and full of red tape, they might not have the wherewithal to do that. So I would take it company by company and it's something you probably should talk to a specific career coach about. So I've been out of the job market for a significant amount of time. How is a career gap perceived by employers? So maybe this is a plus side of the pandemic, but it's actually a little bit more common than you might expect right now for there to be small gaps because of all of the reductions that took place during the pandemic. So you want to be prepared to show what you've done in that time. So did you sit on the beach for six months and enjoy traveling the world? Well, that's great. You want to spin that in a way that won't be off putting. Like they don't want to hire someone for them to quit six months later so that they can go travel the world again. But let's say you've used that six months to attend a boot camp to focus on your learning to make this career transition. That's a perfectly reasonable and acceptable way to show that you what you've done in the career gap. If you had a family situation and you needed to take care of someone else or yourself, whether whatever it might be. You don't have to give details to employer, but you can say you were dealing with family situation and leave it at that. It's resolved, you're ready to get back in the workforce and commit yourself to full time work, which is reasonable. So again, this is something that's probably a little specific, but talk about it with a career coach. They can help you. You don't have to address it specifically, but there are ways when you would probably get questioned about it. There are ways to answer that that doesn't turn off a potential employer. Are there interview opportunities provided as part of Career Services? So here I assume you mean specifically here at Data Camp. So the Career Services team is brand new. We really just launched in March, but we are doing our first networking event or mini career fair coming up this summer, which is really exciting. So. So there will be opportunities to talk to employers. We're looking at having our first one in July and hopefully that's a good motivation for you to get certified because it's only going to be open to individuals who have completed their certification. So you'll get the opportunity to meet with employers, even have someone on one time. If it's a company you're really keen on, it's also a chance for employers to meet you and see if you're a good fit for their company and any potential open roles that they might have. So stay tuned for that. If you're already part of the certification process, I would say get done with it. We want to talk with you here in Career Services and help you get in front of employers. We really want to help you make the career change or get in a data science role. And then I think we have time for one more question or so can you give us an idea on the coding challenges associated with the certification? So the certification is actually a three stage process and what's really nice is the first two stages are very self guided. First, there are skill assessments in six key areas of data science. You can do five of them in either Python or R. Whichever you have expertise in, you can switch it. You don't have to do it all in Python or all in R. You can pick and choose. If you are great at stats but only know it in R. That's fine if you're great in the programming side, but on Python, perfectly reasonable. The sixth assessment is specific to SQL because all data scientists need to have some familiarity with SQL. So that's a dedicated assessment you'll have to do. With those six assessments you can take them as many times as you want there. If you don't meet the minimum required score, it's okay, there's no problem. You can retake it. You can go back to the data camp courses and refresh your knowledge on certain key areas. The good thing about the assessments is that they do highlight areas that maybe you scored a little less on. We really tried to make that as barrierless as possible so it's easy to get through. The second part is a coding challenge. If you've ever taken projects on datacamp, it's like that, only there's a lot less guidance. You're literally given a business problem and a specific data set and you have to write the code out either in Python or in R. And you have to complete the notebook to get a specific answer or specific result. So again, you can keep at it. There's no time, there's no timing involved. So if you need to take some time to work on the coding challenge, you can do that. Once you pass the coding challenge, you gain access to the data sets for a case study. The way the case study works is you're given data sets to choose from. I think there's about 10 or just shy of 10 data sets you can choose from. And you have to create your business problem. Do all of the exploratory analysis come up with. There's usually going to be some machine learning modeling involved and you're going to have to motivate a problem you're trying to solve with your analysis. First, you submit a technical report of all the code that you've created and then the second step of the case study is to do a non technical presentation. That was my very wordy explanation of what's in the certification. But those three steps are really nice because they're really giving you the practical skills by the end of what real life feels like for a data scientist. And the type of work that you'd be doing. And after that, you get access to me and my team so we can work with you on actually finding the job. So I think we're pretty much done here. If you have more questions, you're welcome to email us@careerservicesatacamp.com and it's really been a pleasure talking with you today. And yeah, I look forward to hopefully meeting with some of you one on one soon. Have a good day.