Your mission
As our Data Science Intern (Analytics), you’ll turn raw product and operations data into decisions - building clean datasets, running rigorous statistical analyses (e.g., logistic regression, survival analysis and other statistical models), and surfacing insights that improve acquisition, retention, and unit economics. You’ll work closely with Product, Growth, Commercial and Operations and report to our Managing Director/Co-Founder.
Key Responsibilities:
Analytics pipeline & data quality: Own problem-to-SQL-to-insight workflows; build clean, documented datasets and sanity checks that make metrics trustworthy.
Statistical modelling: Run and explain models (logistic regression for conversion/churn, survival analysis for time-to-event like delinquency or activation); validate with proper diagnostics and calibration.
Experimentation & causal analysis: Design/read A/B tests, apply basic causal inference where tests aren’t feasible; quantify uplift and make clear, action-oriented recommendations.
Product & growth insights: Create cohorts, funnels, and unit-economics views; build lightweight dashboards for weekly rituals (activation, retention, payback).
Communication: Package findings into concise memos/slides; partner with Product/Growth to turn insights into launches, tests, or operational changes.