Senior Manager, Advanced Analytics

Position Summary...

What you'll do...

We are looking for a Senior Manager, Advanced Analytics to lead high-impact analytical initiatives that improve investment discipline, growth strategy, and decision-making across Marketplace and eCommerce. This role will focus on building scalable frameworks to measure incrementality, identify investment inefficiencies, guide marketing and incentive allocation, and translate complex analytical findings into clear business actions. The ideal candidate is a strong analytics leader with deep experience in experimentation, causal inference, forecasting, and business partnering.

They should be comfortable operating in ambiguous environments, structuring complex problems, influencing senior stakeholders, and leading a team to deliver both strategic insights and production-ready analytical solutions. This role requires someone who can move beyond reporting and diagnostics to build decision frameworks that directly shape business strategy, resource allocation, and operating discipline.

Key Responsibilities

Business Partnership & Strategic Influence

* Partner with senior leaders across Marketplace, Marketing, Finance, Product, Merchandising, WMC, and Data Science to understand business goals, diagnose key challenges, and develop analytical solutions that drive measurable impact.

* Translate ambiguous business questions into structured analytical problems, including investment incrementality, marketing and incentive overlap, seller and item prioritization, customer cohort targeting, and the right balance between offer exposure, price competitiveness, and customer experience.

* Provide actionable recommendations to senior leadership based on advanced analytics, experimentation, and causal inference.

* Focus efforts on opportunities with the highest business impact and help leadership make trade-offs across growth, efficiency, and customer experience.

Advanced Analytics & Experimentation

* Lead the design, execution, and interpretation of incrementality studies, A/B tests, quasi-experiments, and causal inference frameworks.

* Develop approaches to measure the true impact of business investments across marketing, incentives, onsite placements, pricing actions, seller programs, and product interventions.

* Apply methods such as randomized experiments, difference-in-differences, synthetic controls, propensity-based approaches, uplift modeling, meta-learners, interrupted time series, and other causal techniques where appropriate.

* Partner with Product, Engineering, Marketing, and Business teams to operationalize test designs, define success metrics, identify treatment and control groups, assess risks, and ensure results are interpretable and actionable.

* Build repeatable experimentation playbooks that help the organization move from one-off analyses to disciplined test-and-learn decision-making.

* Build forecasting and econometric models that explain business outcomes through drivers such as baseline trends, seasonality, pricing, assortment, marketing exposure, offer competitiveness, customer experience, and category mix.

* Develop diminishing returns curves, transfer functions, saturation models, and marginal ROI frameworks to help leadership understand when incremental spend is efficient versus when returns begin to flatten.

* Support annual and quarterly planning by building analytical tools that estimate expected returns, identify risks, and guide spend allocation across programs and channels.

* Evaluate new analytical techniques and determine when they are appropriate for business use, balancing technical rigor with interpretability, speed, and operational feasibility.

* Ensure analytical outputs are robust, explainable, and usable by business stakeholders.

* Lead development of analytical datasets that connect investments, exposures, seller behavior, item performance, customer outcomes, and financial returns.

* Identify gaps in instrumentation, data quality, attribution logic, and measurement methodology. Partner with Engineering and Product teams to improve data foundations where needed.

* Democratize insights through scalable reporting, Looker dashboards, automated diagnostics, and executive-ready business reviews.

Minimum Qualifications

* Bachelor's degree in Statistics, Economics, Mathematics, Engineering, Computer Science, Business Analytics, Operations Research, or a related quantitative field.

* 6+ years of experience in analytics, data science, econometrics, business intelligence, strategy analytics, or a related field.

* Experience leading complex analytical projects with measurable business impact.

* Strong experience with SQL and at least one analytical programming language such as Python or R.

* Experience with experimentation, causal inference, forecasting, econometric modeling, or marketing/investment measurement.

* Experience translating analytical findings into executive-level recommendations.

* Experience partnering with cross-functional business, product, finance, engineering, or data…