Senior Data Scientist

About the role

You will own the end to end delivery of analytical projects that shape product decisions, marketing campaigns, and business strategy at Imprint. You will design and deploy segmentation frameworks and predictive models focused on churn, LTV, and propensity to drive targeting, personalization, and lifecycle optimization across partner programs. You will partner with Product, Marketing, and Commercial teams to support A/B testing and experimentation, designing scalable frameworks and interpreting results to improve LTV/CAC ratios. You will build agentic workflows and AI powered systems that explore data, generate hypotheses, monitor business metrics, and operationalize decisions in production environments. You will translate complex analytical findings into clear narratives for leadership, shaping how the company thinks about growth, partner health, and customer behavior. You will contribute to team excellence through rigorous code reviews, knowledge sharing, and process improvements that raise the bar for the broader Data Science team. You will act as a full stack problem solver, diving into messy data, testing assumptions, and questioning every step in pursuit of the right answer. You will own projects from ideation through deployment and monitoring, collaborating cross functionally to drive measurable impact in a fast moving startup environment.

Key facts

What you'll do

• 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
• Dive into messy data, test and validate assumptions, and question everything in pursuit of the right answer while owning projects end to end
• Partner cross functionally with Product, Marketing, Commercial, and Engineering to drive measurable impact in a fast moving startup environment
• Use strong Python and SQL skills to transform raw data, build custom datasets, and ship models to production at scale

Requirements

• 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.

Practical notes

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Location: New York City

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Engagement: Full-time

• Stack: Python and SQL for modeling and analysis. Snowflake for data warehousing. dbt for data transformation. Sigma for dashboarding. AWS infrastructure.
• Learn more about how we build at Imprint on our engineering blog: https://tech.imprint.co/

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