Hi Everyone, I have 3 years experience in finance industry as analyst. Want to break into datscience (ML) roles in fin tech. I’m practicing python by doing easy leetcode questions and reading statistical learning in R. Any suggestions how should I prepare for the datscience interviews? Also would be great if anyone can share their experience. Thanks a lot! #datascience #dataanalytics #machinelearning #fintech #riskalyze #python #square #stripe #affirm #coinbase #lendingclub #robinhood #paypal #sofi #chime #goldmansachs
This. What @watershed mentioned. There are vast variety of roles. Understand and narrow the role first. You can DM me if you need more info
The title Data Scientist is one of the most abused words in the industry. It can be literally anyone who touches data, ranging from someone implementing recommendation systems into production, someone doing multi arm bandit A/B testing on that recommendation system or someone building a dashboard tracking performance of that recommendation system for business stakeholders. Which of the above three roles are you keen on? The prep varies drastically based on the role.
Thanks for the comment! I’m looking to go in data science which is focused more towards machine learning models.
Okay. The roles where the integrity of ML models matter most will be under what Amazon called Applied Scientist positions. Other FAANGs like FB and Google call them ML engineers or SWE-ML. At many non-FAANGs like Walmart these roles are called data scientists too so read job descriptions carefully. If they ask for familiarity with sklearn and tensorflow, that's what you're interested in. If the role doesn't have a good dose of engineering +ML involved you're likely looking at a research scientist position (which will likely require PhD or relevant experience, light in engineering and heavy on applied research) or it's an analyst role (asking for a lot of Tableau dashboarding) or its a data engineering position (emphasis on database management and orchestration in Airflow etc) The engineering requirements for this role will be fairly heavy especially for FAANGs: study a ton of Leetcode and system design. You'll be facing ML design rounds too so study ranking/relevance/recommendation/NLP etc. This will be dependant on profile you're applying to. If you're already working with data in your workplace, import sklearn and fit some model on it just to say you've done some ML on the resume. The industry is in flux so your mileage might vary with what I've said here but this isn't a bad place to start.