Services LLC

Principal Data Scientist, Topline Forecasting

Job description

  • MSc in Computer Science (Machine Learning, AI), Econometrics, Statistics, or equivalent
  • 10+ years of practical experience applying modeling or machine learning to solve complex problems for large-scale applications
  • Proficiency in at least one statistical software package such as R, Stata, and Matlab
  • Experience with object-oriented programming languages. Experience with Python and AWS technologies is preferred.
  • Expertise using SQL for acquiring and transforming data.
  • Outstanding quantitative modeling and statistical analysis skills.
  • Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences.

Job summary
We seek a Principal Data Scientist to join the core team that utilizes the most advanced statistical forecasting methodologies to provide predictions and insights that enable senior leadership to make key strategic decisions impacting Amazon’s future growth.

You excel at deep diving data, extracting insights and communicating key takeaways to senior leaders. You have thorough understanding of applied time series forecasting and analysis methodologies. You are an exemplary data science practitioner skilled at developing ideas from small scale prototypes to fully mature production-quality solutions. You form strong partnerships with software engineering teams on defining production roadmaps and leading the implementation of complex scientific solutions in production. You make complex trade-offs on scientific and software designs working backwards from the needs of customers. You are a cross-functional leader able to influence a world-class team of Data Scientists, Statisticians, Economists, and Software Engineers to help define problems correctly and apply best practices in tackling these problems at scale.

The position will be based in North America, location is flexible.

Key job responsibilities
  • Apply business judgement to identify opportunities and develop science strategies.
  • Work collaboratively and effectively with engineering and business partners to build algorithms and models for Forecasting and providing business insights.
  • Mentor and grow junior science leaders.
  • Influence, collaborate, and communicate effectively with other engineering, science, and business leaders.
  • Communicate scientific solutions and insights effectively to a senior leadership and non-scientific audience.
  • Develop mechanisms to audit the forecast quality and develop best practices for scientific research.

About the team
Where will Amazon's growth come from in the next year? What about over the next five? Which product lines are poised to quintuple in size? Are we investing enough in our infrastructure, or too much? How do our customers react to changes in prices, product selection, or delivery times? These are among the most important questions at Amazon today. The Forecasting team in the Supply Chain Optimization Technologies (SCOT) organization is dedicated to answering these questions using statistical and econometric methods. We develop cutting edge data pipelines, build accurate predictive models, and deploy automated software solutions to provide forecasting insights to business leaders at the most senior levels throughout the company.

  • PhD in Computer Science (Machine Learning, AI), Econometrics, Statistics, or equivalent;
  • Experience in time series econometrics, causal inference, or deep learning
  • Experience in data applications using large scale distributed systems (e.g. EMR, Spark, Elasticsearch, Hadoop, Pig, Hive)
  • Previously held a technical leadership role for several complete large-scale initiatives

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

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