Senior Data Scientist

Who We Are

Imprint helps the world's best brands grow the lifetime value of their customers. We started with co-branded credit cards and rebuilt them to be smarter, more rewarding, and brand-first. We partner with companies like Crate & Barrel, Rakuten, Booking.com, H-E-B, Fetch, and Shell to launch modern credit programs that deepen loyalty, unlock savings, and drive growth. But the card is just the beginning. We combine advanced payments infrastructure, intelligent underwriting, and deep customer data to create delightful and personalized experiences for members as well as efficient and profitable relationships for our brand partners. Our robust technology and world-class operations allow us and our brand partners to offer powerful financial products without becoming a bank.

In the U.S., co-branded cards alone account for over $300 billion in annual spend, and most still run on decades-old legacy bank systems. Imprint is the modern alternative: flexible, embeddable, and built for how people actually pay today. Backed by Kleiner Perkins, Thrive Capital, Ribbit, and Khosla Ventures, we're building a world-class team to redefine how people pay and how brands grow. If you want to move fast, solve hard problems, and own real outcomes, we want to meet you.

The Opportunity

• Deliver analytical projects that influence product decisions, marketing campaigns, and business strategy, from problem definition through deployment and monitoring

• Build segmentation frameworks and predictive models (churn, LTV, propensity) that drive targeting, personalization, and lifecycle optimization across Imprint's partner programs

• Support A/B testing and experimentation by partnering with Product, Marketing, and Commercial teams to design, analyze, and interpret experiments using scalable frameworks and tooling

• Apply statistical inference, causal analysis, and experimentation design to improve LTV/CAC ratios and accelerate feedback loops on business performance

• Design and build agentic workflows and AI powered systems that explore data, generate hypotheses, monitor business metrics, and operationalize decisions

• Translate complex data into clear narratives for leadership, helping shape how the company thinks about growth, partner health, and customer behavior

• Contribute to team excellence through code reviews, knowledge sharing, and process improvements that raise the bar for the broader Data Science team

Your Profile

Required

• 4 to 7+ years of experience in data science, analytics, or a related quantitative field, ideally at a high growth startup or fintech company

• Degree in a relevant field (statistics, engineering, science, finance, or similar); graduate degree is a plus

• Strong Python and SQL skills, with the ability to transform raw data, build custom datasets, and ship models to production

• Solid foundation in statistical inference, experimentation design, and causal analysis

• Active experience using LLMs and AI tools (Claude, Copilot, Cursor, or similar) as collaborators in your workflow, whether for reasoning about data, generating hypotheses, iterating on analyses, or building agentic automation

• Ability to communicate complex findings clearly to both technical and non technical audiences, including senior leadership and external partner stakeholders

• Full stack problem solving orientation: you dive into messy data, test and validate assumptions, and question everything in pursuit of the right answer

• Comfort owning projects end to end in a fast moving startup environment, collaborating cross functionally with Product, Marketing, Commercial, and Engineering to drive measurable impact

Nice to Have

• Experience in credit, lending, or card products

• Experience building or contributing to experimentation infrastructure or ML infrastructure

• Exposure to lifecycle marketing, prescreen modeling, or customer segmentation at scale

• Background in time series analysis, forecasting, optimization, or simulation

• Familiarity with dashboarding tools such as Sigma or Looker

We don't expect every candidate to check every box. If this role excites you and you bring strong fundamentals, we encourage you to apply.

Stack
Python and SQL for modeling and analysis. Snowflake for data warehousing. dbt for data transformation. Sigma for dashboarding. AWS infrastructure.

Learn More
Learn more about how we build at Imprint on our engineering blog: