Manager, Data Science - Analytics 2

JOB DESCRIPTION

At eBay, we're more than a global ecommerce leader - we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.

Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work - every day. We're in this together, sustaining the future of our customers, our company, and our planet.

Join a team of passionate thinkers, innovators, and dreamers - and help us connect people and build communities to create economic opportunity for all.

Role: Manager, Data Science Analytics - 2

Overview

We are seeking a Senior Manager (Title: Manager, Data Science Analytics - 2) to lead the Shipping Analytics function at eBay. In this role, you will partner closely with the Shipping business, product and engineering teams, leveraging eBay’s vast data ecosystem to uncover insights, influence the Shipping team roadmap, and drive customer-centric innovation across our marketplace.

Shipping sits at the intersection of buyer experience, seller economics, and marketplace growth - influencing conversion, cost, speed, and trust across global transactions.

You will lead a team of talented analysts, data scientists, champion experimentation excellence, and shape analytics strategy for one of eBay’s most critical user experiences - Shipping. This role combines hands-on analytics depth, strategic impact, and leadership responsibility.

Key Responsibilities

1. Strategic Analytics Leadership

Serve as the analytics thought leader for eBay’s shipping product, setting the vision for data-driven decision-making to optimize eBay’s shipping experience.

Partner with Product, Engineering, and Business stakeholders to define success metrics, establish analytical frameworks, and guide prioritization.

Own the end-to-end analytics roadmap for Shipping - from opportunity sizing and hypothesis generation to measurement, experimentation, and impact evaluation.

2. Technical Ownership

Build and scale AI-enabled analytics systems (e.g., automated insight generation, agentic workflows, decision-support tools)

Leverage LLMs and modern data tooling to accelerate analysis and insight delivery

Ability to hypothesize and design experiments, data science simulations to solve complex shipping problems at eBay.

3. Team Leadership & Development

Lead, mentor, and grow a high-performing analytics team; develop career paths and foster a culture of curiosity, rigor, and impact.

Partner with recruiting and analytics leadership to attract and retain top analytical talent.

Provide coaching and technical guidance to ensure consistent analytic quality and scalability across projects.

4. Cross-Functional Collaboration

Drive alignment across product areas, ensuring consistent measurement standards and shared learnings.

Advocate for data democratization by building scalable and trusted data pipelines, self-serve tools, and metric documentation.

5. Operational & Execution Excellence

Evaluate feature and experiment performance, ensuring decisions are rooted in robust data analysis.

Enable rapid insight generation through automation and scalable experimentation pipelines.

Continuously improve analytical workflows and frameworks for speed and reliability.

Set a high bar for analytical thinking, problem framing, and business impact

Required Skills & Experience

10+ years of experience in product analytics, data science, or rigorous analytics roles; 2+ years leading analytics teams.

Deep expertise in SQL, Python, and building AI applications

Strong foundation in statistics, data science fundamentals, and data-driven hypothesis testing.

Proven track record of delivering insights that drive measurable business and product impact.

Excellent communication skills - able to translate data into actionable narratives and influence senior executives.

Demonstrated success in highly matrixed, cross-functional environments.

Preferred Qualifications

Advanced degree in a quantitative field (Statistics, Economics, Computer Science, Engineering, Mathematics, etc.).

Familiarity with big data platforms, experimentation frameworks, and LLM/AI tools

Experience building or influencing data and metric infrastructure for large-scale experimentation systems.

Strong presentation and stakeholder management skills

Additional Details

Explore Location

Close the popup

Save Job