Staff Data Scientist

Staff Data Scientist

The Data team at Imprint builds the data foundation that powers smarter, faster decision-making. The team develops infrastructure and analytics systems that support both daily operations and long-term strategy, enabling high-quality insights into customer behavior, product performance, and business growth.

As a Staff Data Scientist, you will own end-to-end analytical projects that directly influence product decisions, marketing campaigns, and executive strategy. You will apply rigorous statistical methods, experimentation design, and predictive modeling to improve customer lifetime value, accelerate feedback loops, and drive measurable business outcomes.

This role blends deep technical expertise with strong business partnership. You will work across the organization—collaborating with product, marketing, and commercial teams—to design experiments, build segmentation frameworks, and translate complex data into clear narratives that shape how Imprint grows. Increasingly, that means building not just analyses but AI-powered systems that can autonomously explore data, generate insights, and operationalize decisions.

What Success Looks Like in the First 90 Days

• Shipped a new model to production that drives a measurable business outcome
• Delivered a meaningful analysis of a complex business problem, beyond simple A/B test reporting
• Fully integrated with the Data Science team through active participation in code reviews, technical discussions, and knowledge sharing
• Built strong working relationships with key stakeholders and aligned on priorities with your manager and cross-functional partners
• Demonstrated fluency with Imprint's business model, data systems, and user personas—able to explain how the company generates revenue, which partnerships are healthiest, and how your work drives impact

Responsibilities

• Apply statistical inference, causal analysis, and experimentation design to improve LTV/CAC and accelerate feedback loops
• Champion A/B testing by partnering with cross-functional teams to design, analyze, and interpret experiments rigorously, using scalable frameworks and tooling
• Build segmentation frameworks and predictive models (churn, LTV, propensity, etc) to drive targeting, personalization, and lifecycle optimization
• Design and build agentic workflows to automate the data science lifecycle (exploration, modeling, experimentation)
• Use LLMs and AI tools as collaborators to reason about data, generate hypotheses, and iterate on analyses
• Build AI-driven systems for monitoring, diagnosing, and automating business insights and decisions
• Translate data into clear narratives that influence product decisions, marketing campaigns, and executive strategy
• Support automation projects as needed, including anomaly detection, partner data reporting, and internal self-serve tools or dashboards
• Own projects end-to-end - from problem definition through implementation, deployment, and monitoring - while collaborating cross-functionally to drive impact
• Contribute to team excellence through code reviews, technical mentorship, and process improvements

Qualifications

Required

• 7-12+ years (depending on leveling & education) of experience in data science, analytics, or a related field—ideally at a high-growth startup or fintech company
• Graduate degree in a relevant field (statistics, engineering, science, finance, etc)
• Strong Python and SQL skills, with the ability to transform raw data and build custom datasets when needed
• Highly analytical mindset with a bias toward action and a relentless focus on getting the numbers right
• Ability to clearly communicate complex findings to technical and non-technical audiences
• Comfort owning projects end-to-end and collaborating cross-functionally to drive impact
• Full-stack problem-solving orientation—eager to dive into messy data, test and validate assumptions, and question everything in pursuit of a solution

Nice to Have

• Experience building or scaling experimentation infrastructure
• Experience building or improving ML infra
• Familiarity with dashboarding tools such as Sigma or Looker
• Experience in credit, lending, or card products
• Exposure to lifecycle marketing or prescreen modeling
• Background in time series analysis, forecasting, optimization, or simulation

Location & Work Model

• This is a hybrid role requiring 2–3 days per week onsite
• Open to candidates based in or willing to relocate to San Francisco or New York City

Perks & Benefits

• Competitive compensation and equity packages
• Leading configured work computers of your choice
• Flexible paid time off
• Fully covered, high-quality healthcare, including fully covered dependent coverage
• Additional health coverage includes access to One Medical and the option to enroll in an FSA
• 20 weeks of paid parental leave for the primary caregiver and 8 weeks for all new parents
• Access to industry-leading technology across all of our business units, stemming from our philosophy that we should invest in resources for our team that foster innovation, optimization, and productivity

Imprint is committed to a diverse and inclusive workplace. Imprint is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Imprint welcomes talented individuals from all backgrounds who want to build the future of payments and rewards. If you are passionate about FinTech and eager to grow, let's move the world forward, together.