SCOT FBA Science team is looking for an experienced and creative Senior Data Scientist to join our cross-domain science team of data scientists, applied scientists, research scientists, and economists. As a senior data scientist you will be responsible for generating data-driven insights influencing business directions and product/policy designs, building ML models to learn Seller and customer behaviors, and collaborating with business and software teams to solve key challenges facing the worldwide FBA Seller business, including 1) improving FBA Seller inventory efficiency, 2) efficiently balancing the supply and demand of FBA Seller capacity, 3) closing worldwide selection gap by enabling global selling profitability, and 4) driving out costs across the FBA supply chain to spin the flywheel.
Key job responsibilities
As a member of the science team, you will play an integral part in Amazon's FBA inventory management with the following technical and leadership responsibilities:
- Work with product managers, engineers, other scientists, and leadership to identify and prioritize customer and business problems.
- Translate business problems into specific analytical questions and form hypotheses that can be answered with available data using scientific methods or identify additional data needed in the master datasets to fill any gaps
- Design, develop, and evaluate highly innovative statistics and ML models to drive FBA growth and efficiency.
- Guide and establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
- Proactively seek to identify business opportunities and insights and provide solutions to shape key business processes and policies based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams.
- Collaborate with our dedicated software team to create production implementations for large-scale data analysis and/or ML models.
In this role, you will be a technical expert with significant scope and impact. You will work with Product Managers, Software Engineers, and other Scientists, to deeply understand FBA Seller business problems and priorities. You will form hypotheses, analyze Seller and customer data using statistical methods, build new and enhance existing ML models, generate insights and recommendations to address a range of problems on Seller inventory management in order to optimize Seller experience and facilitate their growth. The successful Data Scientist will have extreme bias for action needed in a startup environment, with outstanding leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. It will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term scientific solutions. We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.
About the team
Sellers are a critical part of Amazon's ecosystem to deliver on our vision of offering the Earth's largest selection and lowest prices. Fulfillment By Amazon (FBA) enables Sellers to provide fast and efficient deliver to their customers using Amazon fulfillment services. In 2020, Sellers enjoyed strong growth using FBA shipping more than half of all products offered on Amazon. To our consumers, FBA provides a broad and diverse inventory of products from Books, Electronics and Apparel to Consumables and beyond with many of them available with 1-Day shipping. The FBA Inventory team within the Amazon Supply Chain Optimization Technology (SCOT) organization is the core team in charge of fulfillment services to our Sellers.
"Third-party sellers are kicking our first party butt. Badly. And it's a high bar too because our first-party business has grown dramatically over that period, from $1.6 billion in 1999 to $117 billion this past year. The compound annual growth rate for our first-party business in that time period is 25%. But in that same time, third-party sales have grown from $0.1 billion to $160 billion a compound annual growth rate of 52%. To provide an external benchmark, eBay's gross merchandise sales in that period have grown at a compound rate of 20%, from $2.8 billion to $95 billion. Why did independent sellers do so much better selling on Amazon than they did on eBay? And why were independent sellers able to grow so much faster than Amazon's own highly organized first-party sales organization? There isn't one answer, but we do know one extremely important part of the answer: We helped independent sellers compete against our first-party business by investing in and offering them the very best selling tools we could imagine and build. There are many such tools, including tools that help sellers manage inventory, process payments, track shipments, create reports, and sell across borders and we're inventing more every year. But of great importance are Fulfillment by Amazon and the Prime membership program. In combination, these two programs meaningfully improved the customer experience of buying from independent sellers."
Jeff Bezos, 2018 Letter to Shareholders
- Master's degree in a highly quantitative field: Machine Learning, AI, Computer Science, Statistics, Mathematics, Operational Research, etc.
- 4+ years of hands-on industry experience in predictive modeling and analysis, causal inference, or multivariate statistics, as an ML engineer or data scientist role, applying various ML techniques, and deep understanding the key parameters that affect their performance.
- Strong Analytical skills has ability to scope out business problems to be solved, start from ambiguous problem statements, identify and access relevant data, make appropriate assumptions, perform insightful analysis and draw conclusion relevant to the business problem.
- Proficient with Python and data manipulation/analysis libraries such as Scikit-learn and Pandas for analyzing and modeling data.
- Experienced in using multiple data science methodologies to solve complex business problems (e.g. statistical analysis, research science, machine learning and deep learning techniques, data modeling, regression modeling, financial analysis, demand modeling, etc.).
- Experience with managing large and disparate data sources
- Excellent communication skills. Proven ability to communicate verbally and in writing to technical peers and business teams, educating them about our systems, as well as sharing insights and data-driven recommendations
- A PhD degree in a highly quantitative field (Machine Learning, AI, Computer Science, Statistics, Mathematics, Operational Research, etc.).
- 6+ years' experience in a ML or Data Scientist role with a large technology company.
- Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, data analytics, NLP, deep learning, recommendation systems, information retrieval.
- Experience with AWS technologies like Redshift, SageMaker, EC2, Lambda, & EMR
- Advanced knowledge and expertise with Data modelling skills, Advanced SQL with Oracle, MySQL, and Redshift Databases
- Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.