Fulfillment by Amazon (FBA) is at the core of Amazon’s “Supply Chain by Amazon” vision, enabling hundreds of thousands of Selling Partners to leverage our world-class fulfillment network. FBA helps sellers in 130+ countries send products into our EU network and deliver to customers in 185+ countries, contributing to billions of units shipped in Europe each year. The FBA EU Analytics team is looking for a Senior Data Scientist to own high-impact BI, science and AI initiatives that shape the future of FBA in Europe. You will develop scalable AI solutions — including machine learning models, causal inference frameworks, and optimization algorithms — and deploy them to production to improve seller experience, ensure compliance, and optimize our end-to-end fulfillment economics (cost, speed, and quality). You will partner with Product, Tech, Operations, Finance, and Legal/Compliance across EU and WW to turn ambiguous business problems into well-framed scientific questions and productionized solutions. This is a high-visibility role with direct exposure to senior leadership and the opportunity to work with some of the world’s richest supply chain and marketplace datasets.
Key job responsibilities As a Senior Data Scientist in FBA EU Analytics, you will:
Own end-to-end science solutions : o Translate highly ambiguous, complex business problems into clear scientific hypotheses and success metrics. o Drive projects from concept and data discovery through model development, experimentation, deployment, and post-launch monitoring.
Build advanced ML / AI / GenAI models o Develop predictive and prescriptive models for demand and volume forecasting, cost-to-serve, risk and fraud detection, and inventory / placement optimization. o Apply causal inference, uplift modeling, and experimentation frameworks to quantify the impact of new policies, tools, and FBA programs. o Leverage Generative AI and LLMs for use cases such as intelligent seller insights, document understanding for compliance, automated reasoning over large datasets, and AI-assisted decision support for internal stakeholders.
Shape the AI & Analytics roadmap for FBA EU o Define and drive the Analytics, Data Science, and AI strategy for EU FBA. o “Look around corners” to proactively identify where science and GenAI can create step-change improvements in seller experience, compliance, and operational efficiency. o Prioritize opportunities based on impact, feasibility, and alignment with FBA and Supply Chain by Amazon strategy.
Partner closely with engineering and data teams o Collaborate with Scientists, Data Engineers, BIEs, and SDEs to design data models, feature pipelines, and scalable science services (batch and real-time). o Help define and improve data quality, observability, and model monitoring standards across the team.
Drive experimentation and decision science at scale o Design and analyze A/B tests and quasi-experiments to evaluate new policies, product features, and operational changes across EU marketplaces. o Build reusable experimentation and measurement frameworks for the wider FBA organization.
Influence through narrative and storytelling o Create clear, concise documents and visualizations that “tell the story” of your findings to senior leaders and non-technical stakeholders. o Recommend actions and trade-offs, and influence roadmap and investment decisions using data. o Provide strategic technical guidance to L7+ business partners.
Raise the bar for science excellence o Mentor other scientists, BIEs, and analysts on methodology, code practices, and stakeholder engagement. o Create and deliver best practice recommendations, blog posts, and presentations adapted to technical, business, and executive stakeholders. o Promote best practices in reproducible research, model governance, and documentation.
A day in the life • Start your day reviewing dashboards for a recently launched GenAI-powered insights tool for Sellers, checking performance, drift, and business KPIs. • Join a working session with Product and Operations to refine problem statements for a new initiative to optimize cross-border inbound flows and FBA fees using a mix of forecasting, optimization, and causal inference. • Spend focused time in code exploring new features and model architectures, leveraging AWS services to accelerate EDA, documentation, and hypothesis generation. • Meet with a Data Engineer to iterate on a new data pipeline that will serve both your models and EU leadership reporting. • Draft the architecture of a new ML model that optimizes the fee rate card for EU FBA Sellers across hundreds of product categories and marketplaces. • Contribute to the MBR document with a summary of EU FBA AI Task Force deliverables from the past month. • Present a new code review best practice to the EU FBA Analytics team and clarify adoption expectations.
About the team The FBA EU Analytics team sits at the intersection of science, analytics, and product for the FBA business in Europe. We: • Own core metrics and analytical foundations used by EU and WW leadership to steer the FBA business. • Develop scalable ML, GenAI, and BI solutions that simplify cross-border listing, inbound processes, compliance, and the fulfillment experience for Selling Partners and customers. • Work across EU and global stakeholders in Product, Tech, Operations, Finance, and Legal/Compliance, providing a holistic view of the FBA business.
You will join a diverse group of Data Scientists, Business Intelligence Engineers, and Data Engineers who are passionate about combining rigorous science with pragmatic delivery and measurable business impact.
Basic Qualifications
- Master’s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Data Science, Operations Research, Engineering, Economics, or related discipline).
- 7+ years of industry experience in business intelligence, data science, machine learning, or applied statistics solving real-world business problems.
- Hands-on experience designing, building, and deploying models in one or more of the following areas: Predictive modeling (classification/regression, time series forecasting), Causal inference / experimentation / uplift modeling, Optimization / operations research, Anomaly detection, risk or fraud modeling.
- Strong programming skills in Python (or R) and proficiency in SQL, including working with large-scale datasets.
- 5+ years of experience with big data and cloud technologies (e.g., AWS services such as S3, Redshift, SageMaker, Bedrock, EC2, EMR, Glue, or similar).
- Demonstrated ability to translate ambiguous business needs into analytical solutions and to drive projects end-to-end with minimal guidance.
- Excellent written and verbal communication skills in English, with a track record of influencing senior stakeholders using data.
Preferred Qualifications
- PhD in Computer Science, Mathematics, Statistics, Machine Learning, or an equivalent quantitative field.
- 10+ years of industry experience in data science, machine learning, or applied statistics solving real-world business problems.
- Experience in e-commerce, supply chain, logistics, or marketplace platforms, especially in pricing, cost-to-serve, network optimization, or compliance-related topics.
- Demonstrated experience with Generative AI and LLMs, including: Building or integrating GenAI applications (e.g., text generation, summarization, retrieval-augmented generation, classification, or agents), Designing evaluation strategies and guardrails for AI systems in production.
- Experience building and operating ML models in production (e.g., APIs or services, CI/CD for ML, monitoring and retraining strategies).
- Experience with experimentation platforms, quasi-experiments, and advanced causal inference techniques (e.g., diff-in-diff, synthetic controls, instrumental variables).
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