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ImprintImprintNew York, NY

Staff Data Scientist

Staff Data Scientist owning end-to-end analytical projects that influence product decisions, marketing campaigns, and executive strategy. Applies statistical methods, experimentation design, and AI-powered systems to improve customer lifetime value and business outcomes.

200k – 250k
Hybrid7+ YOEData Science

About the role

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

Requirements

  • 7-12+ years 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

Skills

PythonSQLStatistical InferenceCausal AnalysisExperimentation DesignA/B TestingPredictive ModelingLLMsAgentic WorkflowsMachine Learning Infrastructure

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