Senior Data Scientist
Amazon
Senior Data Scientist
Amazon
Sells products online and rents cloud computing
Do you see a seemingly impossible problem and instinctively think “I can figure this out”? Do you have insatiable curiosity and a drive to turn messy, ambiguous questions into rigorous, data-driven answers? Do you want your analysis to change how one of Amazon’s largest businesses runs its supply chain in Europe?
If so, this role is for you.
Our team owns the most ambiguous and complex analytical problems in EU FBA (Fulfilment by Amazon) Supply Chain. Leaders come to us when a question has no playbook: nobody has defined the problem yet; the data does not sit in a dashboard, and the answer needs both scientific rigor and sound business judgement.
As a Data Scientist on this team, you will define problems as well as solve them. You will design the analytical approach, choose methods from a wide toolkit (statistical modelling, experimentation, forecasting, optimization, and machine learning where it earns its place), and deliver insights that shape supply-chain strategy for our EU marketplaces.
A partner BI team in India owns classic data engineering, dashboarding, and periodic reporting, with support from colleagues in Luxembourg. The role therefore splits roughly 70% science and 30% BI enablement and partner-team support. Your focus stays on advanced, ambiguous data science, but you will also apply strong BI-engineering fundamentals (SQL, pipelines, self-service data, and clear reporting) to unblock yourself, support a newer and more junior partner team, and make your science land in the business.
You will work on problems such as forecasting inbound volumes and fulfilment-center capacity, measuring the causal impact of inbound placement and AWD (Amazon Warehousing and Distribution) adoption on cost to serve and seller in-stock rates, designing and analyzing seller-facing experiments on inbound and value-added services, and optimizing removal and recovery decisions for unsellable inventory. You will also help build generative AI (GenAI) tools and agents that put data science directly into the hands of the business.
You will work closely with product managers, program managers, supply-chain stakeholders, and partner data teams, translating between business needs and technical reality and building consensus on what the data says and what we should do about it.
Key job responsibilities
• Lead complex, ambiguous EU FBA Supply Chain problems autonomously, defining the problem and the solution approach rather than executing a predefined analysis.
• Select and apply the right data science methods (e.g. statistical inference, design of experiments, time-series forecasting, clustering and classification, and causal analysis) to deliver decision-grade insights with quantified impact.
• Partner with product managers, program managers, and supply-chain stakeholders to turn ambiguous business questions into tractable analytical problems, and present results to senior leadership.
• Source and combine complex, cross-domain datasets; write robust SQL and, where needed, build or refine the ETL pipelines and data models your analysis depends on.
• Set standards for reporting and self-service artefacts (e.g. Quick Sight or Tableau dashboards and KPI tracking) and unblock the business where needed, while the partner BI team owns build and run.
• Coach and support a newer, more junior partner BI team: share knowledge, review work, and help raise the analytical and engineering bar across locations.
• Drive best practices in analytical rigor, reproducibility, data quality, and operational excellence.
A day in the life
• Work with stakeholders to understand supply-chain priorities and reframe fuzzy questions into well-posed problems.
• Design the analytical approach, weigh trade-offs between methods, and validate your data, assumptions, and results.
• Write and review SQL and Python and strengthen the pipelines or reporting your analysis relies on.
• Communicate findings in written narratives and reviews for technical and management audiences.
• Mentor partner-team members and unblock BI work that supports the wider organization.
About the team
Our team owns the most ambiguous and complex analytical problems in EU FBA (Fulfilment by Amazon) Supply Chain. Leaders come to us when a question has no playbook: nobody has defined the problem yet; the data does not sit in a dashboard, and the answer needs both scientific rigor and sound business judgement.
- Experience in causal modeling like graphical models, causal Bayesian network, potential outcomes, A/B testing, experiments, quasi-experiments, and data science workflows
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience identifying and solving complex problems through data analysis
- Experience working directly with business stakeholders to translate between data and business needs
- Experience managing, analyzing and communicating results to senior management
- Experience with AWS Tools and Technologies (Redshift, S3, EC2)
- Experience in designing experiments and statistical analysis of results
- Experience with supply chain modeling and other statistical analysis tools
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Experience programming to extract, transform and clean large (multi-TB) data sets
- Knowledge of data visualization tools such as Quick Sight, Tableau, Power BI or other BI packages
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
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Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.
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