About the Company

We have pioneered a new category of consumer credit. By building a credit card secured by real-world assets—including home equity and vehicles—we have fundamentally re-engineered the cost of borrowing. This asset-backed model allows us to offer consumers a dramatically lower APR than traditional credit cards, effectively changing the financial infrastructure for the average household.

We are a well-capitalized team with over $250 million in equity funding, backed by top-tier investors including Founders Fund, Khosla Ventures, and Sequoia. Our team is a blend of technology builders from Microsoft, Facebook, and Azure, and financial executives from Square, CapitalOne, and Goldman.

We are missionaries, not mercenaries. We believe that lowering the cost of capital through technology is one of the most impactful problems we can solve. If we succeed, we build infrastructure that improves lives.

The Role

We are looking for a seasoned Data Scientist to serve as the scientific backbone of the organization. This is not just a reporting role; this is a strategic partnership role. You will sit at the intersection of Product, Engineering, Marketing, and Finance, using rigorous scientific methodologies to inform every major decision the company makes.

In this role, you will move beyond simple descriptive analytics. You will apply statistical, machine learning, and econometric models to massive datasets to measure true causal impact, predict future performance, and design the systems that make the product smarter. You will be the one asking "why" something happened, not just "what" happened.

You will be responsible for defining how the company measures success. From designing and interpreting complex experiments to developing key metrics that provide observability into the health of the product, your work will directly influence the roadmap and the bottom line.

What You’ll Do

1. Shape Strategy Through Science: Partner cross-functionally with Product, Engineering, Marketing, Sales, and Finance to shape strategy using rigorous, data-backed insights.
2. Measure and Attribute Impact: Apply statistical and econometric models to measure outcomes and identify causal impact. The team needs to know what is working, what isn't, and why.
3. Predict Future Performance: Build models to forecast user behavior, product performance, and portfolio health, allowing the company to be proactive rather than reactive.
4. Design and Analyze Experiments: Own the experimental framework. Design tests, analyze results, and translate complex statistical findings into clear, actionable recommendations.
5. Build the Data Foundation: Drive the collection of new data and refine existing data sources. You will work with Engineering to ensure the team is capturing the right signals to power future analyses.
6. Tell Compelling Stories: Create analyses that do more than just report numbers. They will tell a story, illuminate an opportunity, and inspire the team to take action.

What You’ll Bring

1. Experience & Education: 5+ years of data science experience with a proven track record of thought leadership and innovation. A PhD or MS in a quantitative field (e.g., Engineering, Mathematics, Natural Sciences, or Economics) is required.
2. Technical Mastery: Expert-level proficiency in a scientific computing language (Python or R) and SQL. You know how to wrangle large, messy datasets with ease.
3. Deep Methodological Knowledge: Theoretical and applied expertise in statistics, machine learning, and experimental design. You know when a simple regression is sufficient and when a more complex causal model is necessary.
4. Strategic Influence: You have a history of influencing high-impact decisions. You don't just deliver insights; you ensure they are understood and acted upon.
5. Communication Skills: Excellent written and verbal communication skills. You can explain a complex statistical concept to a non-technical stakeholder without diluting the truth.
6. Project Management: Strong organizational skills with the ability to manage complex projects from ideation to production.

Our Tech Stack

1. Languages: Python, SQL, R
2. Data: PostgreSQL, AWS Data Services
3. Infrastructure: AWS

Why Join Us?

This is an opportunity to apply advanced data science to a category-defining product in a highly regulated, high-impact space. You will work on hard, meaningful problems alongside a team of people who built Xbox, Visual Studio, and the earliest CapitalOne credit cards. You will have the autonomy to define the scientific culture, the data to fuel deep insights, and the satisfaction of building a product that materially improves people's financial lives.