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ReSupply · 1 month ago

Statistical Data Scientist

Boston, MA

Full-time

Onsite

Entry Level

2+ years exp

ReSupply is looking for an analytical team player to join us on our journey to reinvent and forever change the supply-chain of charitable contributions within the U.S. The Statistical Data Scientist will work closely with the product development team to enhance user experience and improve product performance through data-driven insights and experimentation.

CharityNon ProfitTransportation

Culture & Values

Responsibilities

Understand how our data is created, stored, aggregated, cleaned, and how it can be used to inform decision making

Apply foundational statistical reasoning to help define and validate product metrics

Think critically about how we define our metrics

Design, run, and analyze the results of A/B tests

Build and maintain clear, reliable dashboards and reports to support new feature development and measure outcomes

Perform analyses on product features to answer open-ended questions and provide strategic recommendations to influence the product roadmap

Architect and maintain data pipelines and queries that serve as the backbone of our product insights and experimentation efforts

Collaborate closely with product and engineering teammates to translate data findings into actionable insights

Qualification

Statistical conceptsSQLPythonA/B testingDashboard buildingData analysisCuriosityAttention to detail

Required

Bachelor's Degree in a quantitative field (e.g., Math, Statistics, Computer Science, Data Science)

Solid understanding of core statistical concepts such as probability, sampling, confidence intervals, hypothesis testing, and the foundations of experimental design

Familiarity with A/B testing principles and measuring product outcomes

Expertise in SQL and working with relational databases

Experience building or maintaining dashboards (e.g., Power BI, QuickSight, Tableau)

At least 2 years of experience with Python scripting through internships/coursework

Experience working on projects that require handling large quantities of data

Curiosity, attention to detail, and a passion for using data to influence product decisions