Data Scientist

Duties And Responsibilities

• Automate in-season KPI reporting and opportunity identification for the referral program to reduce manual weekly reporting effort.
• Partner with Marketing, Product Management, and Product Design to design and execute A/B tests, including instrumentation, test design, reporting, and statistical significance testing.
• Conduct ad hoc, directional, and causal analyses to unblock product decisions and inform business strategy.
• Build new reporting capabilities by establishing end-to-end and product-facing metrics, data pipelines, and dashboards.
• Define key funnel metrics and identify more stable backend metrics to reduce reliance on front-end clickstream data.
• Optimize reporting pipelines and improve business-facing dashboards in partnership with stakeholders.
• Develop self-service experimentation capabilities aligned with testing frameworks used across related product areas.
• Support broader product development initiatives and learning plan development with cross-functional partners.

Required Experience/Skills

• Strong SQL and analytical skills.
• Experience designing, executing, and analyzing A/B tests.
• Knowledge of causal inference methodologies.
• Experience with time series forecasting.
• Industry experience within Financial Technology (FinTech).
• Experience with, or strong interest in, AI-assisted workflows and modern AI productivity tools.
• Proven ability to partner effectively with cross-functional teams to drive data-informed decision making.
• Experience defining business metrics, product funnel metrics, and experimentation frameworks.
• Strong problem-solving skills with the ability to translate analytical findings into actionable business recommendations.
• Experience developing scalable reporting solutions, dashboards, and automated analytics workflows.

Nice-to-Haves

• Prior experience supporting consumer product analytics, FinTech, or growth/product teams.
• Experience building analytics solutions that directly influenced product strategy.
• Enthusiasm for adopting new AI-enabled analytics tools and workflows.

Education

Bachelor's or Master's degree in a quantitative field such as Data Science, Computer Science, Statistics, Business Analytics, or a related quantitative discipline.