# Staff Data Scientist

**Company:** [Imprint](https://hotfix.jobs/companies/imprint)
**Location:** New York, NY, San Francisco, CA
**Role:** Data Science
**Salary:** $200k – $250k/yr
**Experience:** 7+ years
**Skills:** Python, SQL, Statistical Inference, Causal Analysis, Experimentation Design, A/B Testing, Predictive Modeling, LLMs, Agentic Workflows, Machine Learning Infrastructure
**Posted:** 2026-05-21

> 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.

## Job Description

## 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

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