Data Scientist - Analytics

| Greater NYC Area | Hybrid
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Stash is investing, simplified. We are a financial platform that makes it easy for anyone to start with as little as $5. Through education and guidance, we help investors learn the basics so they can confidently save and invest for themselves. At Stash, we are working toward a future where investors are as diverse as our world. 

Stash is looking for a Data Scientist with a passion for building reliable, scalable, and performant data systems and software. We look for strategic thinkers and creative problem solvers with a bias for execution and we’ll expect you to contribute code as well as product/feature ideas from the get-go. If you are looking for a culture that encourages ownership, taking calculated risks, being data-driven and that values evidence over ego, this may be the role for you.

What you’ll do:

  • Build and maintain scalable data systems and infrastructure that empower our marketing, product and business teams to make better decisions 
  • Design predictive models which grow and adapt as our products and customer base scale, utilizing machine learning, time-series and Bayesian statistics
  • Work with large datasets to help us better understand our customers and anticipate their needs through distributed computation techniques
  • Make rigorous statistical inferences from A/B testing on our product and customer segments
  • Normalize our data across institutions and sources using semi-supervised learning

Who we’re looking for:

  • MS in Computer Science, Statistics, Applied Mathematics, Physics, Engineering or a related field with 3+ years of experience
  • 2+ years of professional programming work in Python, Scala, Java, or similar
  • Experience with Pandas, R, or other statistical modeling frameworks
  • An understanding of storing and querying data from Redshift, PostgreSQL, or similar database infrastructures
  • Passion to use all aspects of data science, programming, and technology to build the financial advisor of the future
  • Experience using machine learning to improve algorithmic systems
  • Comfort with distributed computing, specifically Pyspark, AWS EMR, and Airflow
  • Knowledge of Looker or similar front end analytics platforms
  • Data Engineering and ETL experience is a big plus!

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We believe that diversity and inclusion are essential to living our values, promoting innovation, and building the best products out there. Our success is directly related to the employees that we hire, grow and retain and we believe that our team should reflect the diversity of the customers that we serve.  

As an Equal Opportunity Employer, Stash is committed to building an inclusive environment for people of all backgrounds. We do not discriminate on the basis of race, color, gender, sexual orientation, gender identity or expression, religion, disability, national origin, protected veteran status, age, or any other status protected by law. Everyone is encouraged to apply.

Benefits & Perks:

  • Equity in Stash                           
  • Flexible Vacation
  • Family-Friendly Medical, Dental, and Vision Insurance Plans
  • 401k
  • Learning & Development Stipend
  • Commuter Benefits and Flexible Spending Account (FSA)
  • Employee referral bonuses
  • Stocked fridges & kitchens and catered lunch on Fridays
  • Thursday happy hours  
  • Team outings that do not involve trust falls...

Awards & Recognition:

  • Forbes Fintech 50 (2019)
  • LendIt Fintech Innovator of the Year (2019)
  • Built in NYC's Best Places to work (2019)
  • Built in NYC’s Startups to Watch (2018)
  • Wall Street Journal's "Top 25 Tech Companies To Watch" (2018)
  • MarCom Awards Double Gold & Platinum Winner (2018)
  • Webby Award Winner for Best Mobile Sites & Apps in the Financial Services and Banking category (2017)
  • W3 Awards Winner for Best User Experience (2017)

**No recruiters, please.

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Location

We offer employees the choice and flexibility to work where you want from anywhere in the US or UK. We offer stipends to make home offices productive and for those who don't live near our NYC and London offices, to secure space when they want it.

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