Data Science Manager
First seen by Alion on Sep 3, 2026.
About the team and the role :
The Consumer-to-Consumer (C2C) team focuses on creating a simple, safe, and engaging selling experience for eBay sellers - from listing and shipping to getting paid and growing their side-hustle. Within this space, the Analytics team plays a central role in shaping product and business strategy and in guiding decisions that influence the product roadmap and marketplace performance.
As Manager, Data Science - Analytics 1 in the Indian Analytics Centre, you will support the analytics strategy for C2C M&A integrations. This role combines hands-on technical work with strong cross-functional collaboration. You will partner with product, engineering, peer analytics teams, and business stakeholders to deliver scalable data solutions, advance experimentation practices, and develop AI-enabled tools that improve decision-making and seller outcomes.
What you will accomplish :
- Support C2C product analytics and experimentation strategy for M&A integrations.
- Support the leadership team in measuring, understanding, and driving success for eBay sellers through data science analysis, reporting, and competitive intelligence.
- Define and implement consistent metrics, experimentation frameworks, and measurement standards to support data-driven decision-making.
- Support AI-focused initiatives by prototyping and delivering data products and tools that enhance product performance and automate analytical workflows.
- Establish high standards for data quality, instrumentation, and metric definitions, aligning data architecture and semantic layers across teams.
- Own business performance tracking through domain scorecards, support regular reviews, and translate insights into clear recommendations for leadership and stakeholders.
- Partner with product, engineering, and business stakeholders to prioritise initiatives, remove bottlenecks, and deliver impactful outcomes.
- Develop scalable processes and solutions that improve the speed, quality, and effectiveness of analytics across the organisation.
Required qualifications :
- Bachelor's or Master's degree (or equivalent practical experience) in Statistics, Economics, Mathematics, Computer Science, Engineering, or another quantitative field.
- 7+ years of Experience.
- Strong hands-on SQL skills, including experience working with large and complex datasets.
- Ability to create intuitive, user-friendly dashboards and data visualisations using appropriate BI or analytics tools, with a strong focus on usability, clarity, and actionable insights.
- Exposure to A/B testing, causal inference, or quasi-experimental methods.
- Experience in product analytics, including funnel analysis, feature adoption, customer behaviour, performance measurement, and insight generation.
- Strong analytical and problem-solving skills, with attention to data quality, metric definitions, and methodological rigour.
- Ability to connect data with product and business context and convert findings into clear, actionable recommendations.
- Effective written and verbal communication skills, with the ability to collaborate across product, engineering, business, and analytics teams.
- Ability to manage multiple priorities, work independently, and deliver high-quality outcomes in a fast-paced environment.
- An AI-first mindset and interest in using AI tools to improve analytical productivity and decision-making.
Good to have :
- Demonstrated experience contributing to product or business strategy in previous roles, using data and insights to identify opportunities, shape priorities, and influence roadmap decisions.
- Proficiency in Tableau, with experience creating intuitive dashboards, scorecards, and self-service reporting solutions.
- Working knowledge of Python for data analysis, automation, or prototyping.
- Experience with product analytics platforms such as Mixpanel, Amplitude, or similar tools.
- Experience in e-commerce, online marketplaces, consumer technology, payments, or seller-focused products.
Skills
Data Science, Data Scientist, SQL, Python, Business Intelligence