Data Scientist, Growth at Point (W19)
Brings rewards and benefits to the debit card.
San Francisco, New York, Remote
3+ years
About Point

Point is bringing the rewards and benefits of elite credit cards to your everyday debit card.

About the role

Point is a technology and design company that transforms everyday spending into a delightful and rewarding experience. We’re re-thinking the payment experience with an emphasis on transparency, delight, and personalization.

With the best benefits of both debit and credit, Point Card earns you points on every purchase redeemable for instant cash-back. Point App works side by side with Point Card to create an elegant, easy-to-use experience.

We recently closed our $46.5 million Series B funding round. To learn more, see TechCrunch's coverage here.

Backed by top investors like Peter Thiel (Valar Ventures) and Y Combinator, we’re well-funded and ready to make a positive impact on people’s daily lives.

We’re looking for a  Growth Data Scientist  to join our specialized team. We have the vision and resources, and need your talent and skills.

Who we're looking for

Point is looking for Growth Data Scientist to join our focused, growing, and passionate team. We want data scientists who approach problems from first principles, are comfortable diving into disparate external datasets to uncover actionable insights, enjoy optimizing marketing spend & onboarding funnels, and thrive with a fast-paced product iteration cycle.

What we'll build together

As the first Growth Data Scientist at Point, you'll help us improve & optimize our marketing spend & membership conversion by testing hypotheses and surfacing key insights to leadership.

You'll perform deep analytics on large datasets from a myriad of internal and external data sources, build models to describe and predict marketing efficacy and conversion behavior, and produce insights that shape key decisions & investment areas.


  • 3+ years of analytics experience & data science or equivalent applying quantitative, statistical & machine learning technique to improving product growth & adoption
  • Fluency with data analysis programming languages (Python / R), SQL, & data visualization tools
  • Comfortable analyzing external data with uncertain quality and producing well understood, qualified results
  • Familiarity with data warehouse design, development, and ETL best practices
  • Strong verbal and written skills to explain technical analysis to non-technical partners

Bonus Points

  • Fintech or cryptocurrency experience, especially at a venture-backed startup
  • Experience using orchestration tools (like Airflow) and dashboarding tools (Metabase, Mode, etc.)
  • Experience with cohort and funnel analytics, and a deep understanding of statistical concepts including probability distributions and selection bias

Point Perks

  • Join a fast-growing brand that is building thoughtful spending products.
  • Competitive salary, stock options, and 401K.
  • Full health benefits (medical, dental, and vision insurance).
  • Unlimited vacation policy, paid company holidays, and WFH flexible. We shut down the office at the end of the year for a winter holiday.
  • Free Point Card membership + 10,000 ($100) monthly points.
  • Monthly stipends on your Point Card to use for lunch, commuting, and other essentials.



Point’s tech stack consists of bleeding edge tech like Node.js, Apollo GraphQL, AWS Lambda, AWS Kinesis Streams, Prisma ORM, and AWS Aurora Postgres, but we are always striving to use the latest tools cut out for the job at hand! 

Working on a modern finance product comes with its unique set of challenges. Operating in a heavily regulated domain with many moving pieces, we partner with high quality vendors that enable us to offer services like deposit accounts and debit cards. This means we must build our systems with redundancy to third party risk. Simultaneously, being an innovative financial product there are many different elements of the stack we must build ourselves, especially on the rewards side of things — this gives us creative freedom to offer a highly differentiated product.

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