Manager, Data Science – Analytics

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.

Job Description – Manager, Data Science – Analytics

The Incentive and loyalty team works closely with product and business partners with the objective to drive success of eBay’s key marketing investments through data-driven recommendations, we are a dynamic and driven team working on high impact projects along with partners from global teams.

We are seeking a high-energy, driven and collaborative team member with extensive problem-solving skills, sound business judgement and deep analytical capabilities. The ideal candidate will apply advanced analytics and data science techniques to drive innovation, build data products, and deliver actionable recommendations through meticulous analysis.

Responsibilities:

• Demonstrate strong analytical and statistical skills towards taking complex and unstructured business problems, wide variety of quantitative and qualitative data, and provide structured and data-supported practical solutions to optimize eBay’s domestic and cross-border shipping operations.
• Drive product decisions through A/B testing techniques to improve shipping time estimates, routing, cost reduction while optimizing conversion.
• Serve as a trusted partner and advisor to business units and senior leaders, translating complex analytical results into business insights, create necessary tools/reports to monitor and ensure program success.
• Collaborate with cross-functional teams, including business unit, product management, engineering, and finance, to identify, prioritize, and solve shipping-related business challenges.
• Drive innovation and continuous improvement within the Incentive and Loyalty analytics team, develop data products for faster and accurate decision-making, leverage advanced analytics tools and data science models.

Additional requirements: This role operates within a hybrid work-from-home model, requires flexibility for late evening audio or video conference meetings with US or Europe-based partners, or respond to emails and complete tasks in late evenings.

What we expect from you:

• Bachelor’s degree in Engineering, Computer Science, Economics, Statistics, Mathematics, or a related quantitative field. Master’s in a related field or MBA is preferred.
• 8+ years of work experience in data science, analytics, or a related field.
• Strong analytical skills with expertise in SQL, Excel and data visualization tools (e.g. Tableau), Proficiency in a statistical programming language like R or Python is preferred
• Background in product analytics with hands on experience with A/B experiments (design and measurement techniques) is preferred.
• Proven track record of using data science / analytics to drive significant business impact, build predictive models, tackle elasticity and optimization problems.
• Excellent communication skills, with the ability to translate technical concepts into actionable insights for non-technical partners.
• Experience working in a fast-paced environment with cross-functional teams

Basic checks:

• Educational background – Bachelor’s in engineering, CS, Statistics, quant field
• 7-10 years of experience, majorly spent in analytics and data science role
• Some keywords to look for – “data science”, “analytics”, “A/B testing”, “product analytics”
• Tools: SQL, Python and at least 1 reporting tool like Tableau/ QlikView/ Power BI
• Some experience in similar companies – ecommerce/ retail would be good
• Good to have but not necessarily – MBA, good colleges
• Mentioned business impact from their work

Candidate check:

• Hybrid role, working with global partners which means late night calls