Staff Data Scientist – Business Analytics

Posted 2ds ago

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Job Description

Staff Data Scientist focused on business analytics for an e-commerce platform. Leading strategic analytics and causal measurement to optimize growth initiatives and improve decision-making.

Responsibilities:

  • Design and maintain forecasting frameworks for revenue, GMV, merchant growth, and other key business drivers
  • Lead opportunity sizing for new products, pricing changes, market expansions, and strategic initiatives
  • Build causal impact measurement capabilities (e.g., synthetic control, diff-in-diff, geo-experiments) to quantify the true ROI of business investments
  • Develop and maintain a repeatable measurement playbook that standardises how the company evaluates bets — covering incrementality, attribution, and counterfactual reasoning
  • Create merchant and customer segmentation and scoring models that drive prioritisation across sales, marketing, and merchant success
  • Define decision-grade metrics and KPIs in partnership with Finance, Commercial, and Product leadership
  • Translate complex analytical findings into clear, actionable narratives for C-level and cross-functional stakeholders
  • Mentor analysts and data scientists across the team on statistical methods, causal inference, and analytical rigour

Requirements:

  • 7+ years of experience in product analytics, data science, or applied statistics at a technology company
  • Deep hands-on experience designing, running, and analysing A/B tests at scale, including familiarity with common pitfalls (SRM, peeking, metric sensitivity, novelty effects)
  • Strong understanding of event-tracking architectures and instrumentation best practices (e.g., event taxonomies, naming conventions, schema governance)
  • Expert-level SQL and Python (pandas, scipy, statsmodels, or equivalent)
  • Solid statistical foundation: hypothesis testing, confidence intervals, power analysis, multiple comparisons, and causal reasoning
  • Experience defining and maintaining product health metrics, guardrail metrics, and north-star metrics
  • Proven ability to synthesise experiment results and product data into coherent strategic narratives for product and engineering leadership
  • Excellent communication skills, with a track record of influencing product decisions through data.