Join one of the fastest growing rewards/fintech startups in the world - Benjamin! Backed by Play Ventures and F4 Fund, we're all about making everyday actions rewarding. We're looking for an experienced Data Scientist to help us take things to the next level.
At Benjamin, we give users real cash rewards—what we call MoMos (Money Moments)—for things they’re already doing. From playing games and watching ads to everyday card purchases with cash back, we’re all about putting money back in people’s pockets.
What you’ll do
- Find and frame the high-impact problems, figure out which lever moves the metric before writing a line of model code, so every project has a clear "so what?"
- Optimize rewards and incentives directly — uplift modeling and reward/pricing optimization that grows engagement and conversion without wasting spend
- Recommend and rank offers and content in real time — the right offer for the right user at the right moment
- Own experimentation and measurement across product and paid acquisition — causal impact, incrementality, and attribution (MMM and multi-touch)
- Take problems zero-to-one — turn a blank-slate idea into a production data product, not a Confluence page
- Build features, labels, training datasets, and evaluation pipelines
- Ship models as batch jobs, APIs, services, or product features — and keep training, validation, and inference running reliably without hand-holding
- Mentor the team and set the standard for ML engineering at Benjamin
What we’re looking for
- Strong statistical judgment: you know experimentation, causal inference, and model evaluation cold, and you use them to decide what's actually working
- A track record of models that moved a real business metric. You frame problems around impact and can answer "so what?" about your own work
- Experience with recommendations, ranking, forecasting, uplift, or causal methods
- You've operated reliable pipelines in production, not just built them once
- Comfortable getting your own work into production — cloud (AWS preferred), a warehouse (Snowflake, BigQuery, Postgres, or similar), and enough software engineering fundamentals (Git, testing, CI/CD, Docker) to ship without hand-holding
- Bias toward simple, practical solutions. Strong communication and ownership
Our stack
- Data: Snowflake, BigQuery, Postgres, dbt
- Cloud/infra: AWS (GCP), Terraform, Docker
- Languages: Python, SQL, TypeScript
- Tooling: Hex, GitHub Actions, Git, Airbyte, Claude
You won't have used every tool here, and you don't need to. Strong engineering fundamentals and experience operating production data systems matter more than matching the stack.
Why Join Us?
- Competitive pay: We offer great salaries and bonuses.
- Thriving in Hyper-Growth: Immerse yourself in the dynamic environment of a hyper-growth startup, where you'll encounter daily challenges and avenues for professional advancement.
- Cutting-Edge Collaboration: Engage with innovative technology and join a fast-paced team known for its forward-thinking approach and commitment to innovation.
- Positive Workplace Culture: Experience a professional yet enjoyable atmosphere, where hard work is valued alongside a sense of humor and camaraderie, fostering a fulfilling work environment.
About Benjamin
Benjamin is reshaping the future of cash rewards with a simple idea: everyday actions should earn you cash. Whether you’re making a purchase, playing a mobile game, or watching an ad, you get rewarded with Benjamin Money Moments. It’s that simple.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
About Benjamin
Benjamin is reshaping the future of cash rewards with a simple idea: everyday actions should earn you cash. Whether you’re making a purchase, playing a mobile game, or watching an ad, you get rewarded with Benjamin Money Moments. It’s that simple.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
