Staff Data Scientist - Experimentation & Applied Modeling - Marketplace

Senior Data Science Analyst Founding member, India Product Development Team Bengaluru (Hybrid) - Individual Contributor - Full-time About the Opportunity: Our client is a global, AI-driven marketplace platform (publicly listed, headquartered in the US) that connects businesses around the world with a large network of specialized service and fulfillment partners, providing instant pricing, decision-support, and technology-driven solutions at scale. They are now building their first Product Development Team (PDT) in India, a founding team that will own core global platform areas end-to-end and help set the culture, practices, and standards for the org as it scales. This is a full-ownership build, not a support or augmentation function. We (all things talent) are managing this search end-to-end on our client's behalf. About the Role: This is a Staff-level, individual-contributor Data Science role, not a generalist metrics-and-dashboards position. You will own data science for a key global product and business area, spanning experimentation, causal analysis, and applied modeling, while also mentoring other data scientists and setting the experimentation bar for the India team. Indicative Time Split: - 40% - Experimentation design and execution - 20-30% - Data science applied to long-run product analysis (identifying opportunities and problems) - 30% - Metrics, business reviews, and analytics How You'll Contribute: AI-Driven Analytics: - Champion the adoption of AI across the analytics lifecycle, finding new ways to accelerate data science work across the org. Analytics & Business Insight: - Define metrics that measure product and business performance. - Analyze data to identify opportunities, issues, and key business drivers. - Turn insight into clear, actionable recommendations with estimated business impact. - Build dashboards and visualizations that track performance and trends. Experimentation & Statistical Inference: - Design experiments end-to-end to measure the impact of product and business changes, not just run them. - Apply statistical and causal inference methods (power analysis, Bayesian methods, diff-in-diff / pre-post analysis) to draw reliable conclusions. Modeling & Technical Leadership: - Apply data science techniques such as clustering and segmentation to surface product opportunities. - Work with large datasets on cloud platforms (e.g., AWS, Snowflake) using SQL, Python, and BI tools. - Partner closely with Product and Engineering to shape strategy and priorities. - Set a high technical bar and mentor other data scientists across experimentation and modeling. Founding & Scaling the India Team: - Serve as a founding member of the India Product Development Team, helping establish strong data science practices from the ground up. - Build trust and working rhythms with global stakeholders and cross-functional partners. What You'll Need: Must-haves: - 8+ years of progressive data science experience, with meaningful time in a senior IC (staff/principal) capacity. - Direct experience working embedded within a product team, not purely ad-hoc business or strategy analysis. - Real, hands-on experimentation experience beyond basic A/B testing, you should be comfortable discussing power analysis, Bayesian methods, and diff-in-diff / pre-post analysis. - Genuine comfort with an individual-contributor path. This is an IC role today, with the possibility (not a guaranteed timeline) of moving into people management as the team scales. - Proficiency in Python (pandas, numpy, SciPy, scikit-learn) and strong grounding in statistics and linear algebra. Good to have: - Background in consumer, e-commerce, payments, or two-sided marketplace businesses. - Experience in a US-headquartered company or Global Capability Center (GCC). - Master's or PhD in a quantitative field (applied math, computer science, statistics, engineering, or related). - Familiarity with reproducible, versioned scientific/analytics workflows. What's on Offer: - A true 0-to-1 mandate: help build a founding team and its practices from day one. - Full ownership of a global platform area, not a regional or India-only mandate. - Close partnership with senior product, engineering, and data leadership across geographies. - A genuinely AI-forward way of working, in the product and in the team's own workflow.