How to Pivot and Advance Your Data Science Career | Facebook Data Scientist | Data Science Career

hey guys welcome back to my channel in this video i'm gonna interview one of my subscribers jesse jesse was the data scientist at microsoft and she was able to land multiple job offers in a recent job search she has accepted an offer with facebook and has just joined it as a senior data scientist in this video jesse will share with us all the useful tips and resources she has found helpful in her own job search on top of that she will also share with us valuable career advice to advance your data science career advice that i wish i had access to when i was early in my career so let's get right into it hey jesse thank you so much for joining me today i am so excited to have you here on my data interview pro channel thanks emma i'm really excited to be here thanks for having me i have been an audience for your youtube channel for quite some time now and you're actually both on youtube and medium so thanks for the opportunity to share my personal experience and hopefully contribute a little back to the community thanks jesse i know that you recently went through several data science interviews with different companies and you have successfully landed multiple job offers including facebook where you will be joining soon so how about you actually take the runes on this jesse that you introduce yourself and just give us a brief overview of your background and your journey yeah um so my name is jessie and i've been working data science analytics field for about eight years now i actually started off in consulting being mainly focused on 2b business made the switch to tacx several years ago i was the original analytics lead for expedia's b2b partner business and most recently i'm part of the microsoft cloud data science team with an emphasize on cloud security and infra products so i recently actually went through a couple interviews i focused on the data science analytics track and i also made attempts to interview for product manager as well but happy to share um some of my learnings today before we get started i kind of want to call out that interviews are really tough today for most people it is for me as well even though i have eight years of experience now um so if you feel like you're struggling you know you're not alone on this journey that's actually one of the main reasons i want to shoot this video with emma today is to kind of really team up and support each other along the way yeah that's really the goal of this video and i like that you pointed out that interviews nowadays are not easy and i can totally relate to that many people reach out to me to get help in getting interviews and preparing for interviews and in today's video you will be sharing with us some useful tips and resources and we will get into all of those for sure but before we talk about the success you have i'm just very curious since you mentioned that you have a background in consultation how do you see the difference working as a consultant versus working as a data scientist in the tech industry yeah so i had four years of experience in consulting before i started at expedia i think one of the main reasons i started my career in consulting is that i want to have really big exposures on different projects so usually when you're in consulting and i was part of the um factorial and analytics track is that you get to try out different projects uh usually you're on the rotate every couple months you get to team up with people from different locations um so it's really cool to be you know for one traveling a lot to the client side and have that face-to-face um kind of stakeholder management experience and um so i thought that was really cool i think the biggest uh difference that i personally noticed is that you really get to see kind of the progression of your projects from end to end when you switch to when i switch to tech you know i kind of were participant in kind of the the visioning and really building up the roadmap for a feature and then you actually get to develop it um so it's more of a long-term process and you also get to see how you the products that you build gets adopted so i think that's something that was really attractive and you know sounded very rewarding adventurous to me so that i made the switch do you feel your consulting experience helps you with making the transition into tech or those two are totally different and you have to learn from scratch yeah so i have four years of experiencing management consulting one of the key differences i thought was that on consulting you get to try out many different projects you get to travel to clients that also helped with the stakeholder management and experience and also working with different teams and with different backgrounds so i thought that was really actually really helpful in terms of making the transition to my first row at expedia is that i get to really partner closely with my stakeholders that sits in product team engineering team and sales organization so that's something that i thought was a good transition coming from consulting to tech it also helps on kind of the framing and thinking about kind of how you approach a problem how you kind of structure it to really get get it um kind of drive forward so that was also the second point i thought it was helpful cool i think it gives people courage to make a transition from a consulting background to working as a data scientist in the tech industry now let's dive into your success story of being able to land multiple job offers in a recent job search in fact i want to share the story about how we get to know each other i remember you reach out to me by a contact form i put up on my youtube channel a few months ago and you shared with me some challenges you were facing learning product and av testing because you did not have much experience in those areas and you asked me if i was willing to do a mock interview for you i really wanted to help you so we did a mock interview together and i remember you were definitely one of the top performers that i've done mock interviews and real interviews with and even though you told me you did not have lots of experience on customer facing products you did so well in the mock interview your answers were very structured and in-depth obviously you did lots of preparation before the mock interview so no surprise at all now you got multiple job offers could you share with us how you prepare before the mock interview yeah um so actually when i had the actual mock interview with you i have probably already done a 15 to 20 mock interviews with my study group um so that was one thing that was really key is that i treated the mock interview with you very seriously and i treated it as a as a real interview i remember i was i was i was getting a little nervous waiting for your call um but i think the key and i try to summarize a little bit here is um i tried to make sure that i feel prepared um coming up to to do the mock interview with you and i think before that i tried to mock interview with other people um and it's really kind of three steps that i've taken uh the first one is to really draw um experiences from my projects and my my experience um to really understand uh which path i want to go because for data science it's a really broad subject and i personally wanted to go down the path for kind of analytics and inferences and then i used a lot of your youtube content videos for the data science analytics fundamentals on like stats and coding and a b testing and product sense that was really helpful as well so i actually did all of that preparation work before i had my mock interview with you yeah it sounds like you did lots of preparation and you treat it very seriously i really like that because based on my observations people who do great in mock interviews are those who take it seriously you also mentioned that you've done a bunch of mock interviews before the one with me i'm curious how do you find people to do mock interviews with yeah so i feel very lucky i have friends who are also data scientists at different tech companies so i have reached out to them uh maybe two or three people that i specifically set time to um went through some of my kind of struggles or some of my points where i feel like i didn't get enough exposure on my day-to-day job i i have probably two to three years of experience directly on like product and fraud and and but it wasn't that much right but and i was interviewing for kind of a senior role so i set time with them who already have experience in the industry uh in addition to that i also asked for kind of forming study groups online on like online forums um and they were also friends my friends were also product managers and business analysts we um prepared uh maybe once or twice every every week on the weekends wow you're a great example of practice makes perfect so for others who also want to leverage mock interviews to fast track their interview preparation what advice would you have for them yeah i think really um like practice a lot and treat it seriously um i i think and not only to mock interviews it's to any questions um like for example it could be like a behavioral question or like a project highlight um like write it down and like maybe use the voice memo and um listen back to it and see if there are things that can be improved um like was it really concise was it structured really well especially for mock interviews i think for a product sense question um i leveraged a lot from this uh other channel uh in addition to yours called exponent um they have it's mainly for product managers but i found it really helpful for data scientists especially analytics track to think like a product owner so that you have um you know it's more about your structure and framing and your logical thinking of how you decomponentize everything versus the actual product ideas which you know you might not have a lot of exposure to myself included um so i thought that was really helpful i think thinking back that my consulting background was also helpful in the business acumen and businesses questions that that was kind of relatable those are really great tips thank you for sharing other than doing mock interviews to practice your product knowledge are there any other tips or suggestions you have for people who lack experience in developing customer-facing products but want to land a job in a b2c company or product driven company yeah and and that was actually one of my pain points as well as i was preparing for it early on is i didn't feel really confident because i don't have that many years of experience in indirectly part of facing uh development work for from data science perspective um but i was thinking that you know we are we are all customers as well so next time when you're ordering food from doordash ordering delivery from um you know instacart or posting your next uh instagram uh stories uh or or even calling you know uber um maybe you can think about you know how was this experience uh was it smooth at each step of the way did you notice any latency issues you know from a backhand system perspective were there any errors that thrown out like if there are any ways you think you can provide feedback to the developers um sometimes i personally gotten feedback uh hear back from them to kind of uh thank my um your suggestions and that they're improving on it so i think um even if you don't have a lot of direct product experience you can try to pivot um the other way around and think from a user customer's perspective and try to have some brainstorm experience uh maybe with yourself or with your friends um that you can feel relatable to um i think that to the point if you can have those products as a conversation more like a discussion versus an interview where you're trying to find the right answer i think that's that's when you're you know you've nailed it i love that i'm glad you mentioned that even though if you don't have direct work experience you could always think about ideas to improve products from a customer's perspective it's very helpful to develop your product sense on top of that one commonly asked question in data science interviews is about how to improve a communist product if you have this kind of practice on a regular basis it will help you with having a deep conversation with the interviewers during interviews i think this tip would be really helpful for everyone who's listening so are there any other tips you want to share with our audience to prepare for data science interviews or to learn data science in general yeah happy too i i think one of the first things i did was to really find out which path i want to go you know data science you have a lot of choices it's a very broad subject and so i think picking your career path is really important to understand do you want to interview for analytics track or do you want to go for mle or do you want to go for a software engineering developer who are focused on ml um so that those are different things that you want to really figure out before you apply uh java applications um and then a couple things i also spend a lot of time on is to really spend time and think back do a respect a retrospective and do a write down a project that you feel really proud of um that you want to highlight on i think finding something that really motivates you and that you're really passionate about is really key to like being able to find the right next role and play to your strengths um i i have read some blog posts as well so it's not really related to any um kind of uh technical uh doubts or execution it's something more about like thinking from a broader picture and understanding where you are at different stages of your career i cannot agree with you more my philosophy is also to find one direction you are really passionate about and focus on it in that way you feel less overwhelmed and you are more efficient to learn the job offer and be good at it so jesse thank you so much for sharing all those helpful tips and suggestions are there other words of wisdom you want to share with our audience today yeah um so sharing a little more on my personal um kind of uh retrospective is i i think sometimes i um even myself i've underestimated the importance of communication skills i think sometimes people like to call it soft skills but it's really important and it's kind of hard to gain as well especially if you are early on in your career to you know not only focus on the technical depth and execution but also thinking um about how you can grow the skills to work across different functions to try to deliver message uh from people with different audiences and different backgrounds to really help drive the projects forward together um i think um you know being a good listener try to have empathy uh try to have find those common grounds so that you can partner with other teams those are also very important skills to have i think in addition to that this is something i've recently picked on i think over the last few years as well is to you know try to build your personal brand and reputation i think that if you can in any way to become a you know smee in a domain knowledge doesn't have to be a big feature that you own but if you can help grow a domain knowledge and become the expertise in that area that people will kind of come to you and you'll be known for a certain domain and i think that kind of linking back to my early point is really to find something that you're passionate about right so i think those are you know maybe just two things i want to highlight before um before we close up this is so insightful totally agree with you on that soft skills are important in your day-to-day job as a data scientist especially when you collaborate with other professionals in a coming on some cross-functional projects also i want to echo what you've mentioned on building a personal brand to become the go-to person and the expert in a specific area or domain that could help you advance your data science career thanks so much jc for your time i really appreciate you joining me today to share all of those useful tips and learnings yeah thanks for having me um and best of luck on finding the next rope

Channel: Data Interview Pro

Views: 5,241

Keywords: facebook data science, facebook data scientist, data science career, data scientist career

Id: Vc93qY2i-tg

Length: 17min 18sec (1038 seconds)

Published: Tue Sep 14 2021