Senior Manager Data Science
About the job
Amazon Web Services (AWS) provides companies of all sizes with an infrastructure web services platform in the cloud (“cloud computing”). With AWS you can requisition compute power, storage, and many other services – gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading platform for designing and developing applications for the cloud and is growing rapidly with hundreds of thousands of companies in over 190 countries on the platform.
The WW Revenue Operation and Data Analytics team is looking for a Data Scientist Leader to manage our science team. This leader will work closely with business stakeholders to automate recommendations by creating various tools and machine-learning models to answer complex business questions and provide insights. You will manage a team that provides predictive research, analytics, and insights to sales organization, including actionable activities to address existing business questions and opportunities, and collaborate with field sellers, specialized sales, marketing, sales operations, and finance. You need to be a sophisticated user of advanced quantitative techniques for answering specific business questions, and an expert at synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication. In addition, the leader must possess excellent interpersonal skills, strong written communication skills, be able to develop and mentor people, and oversee a portfolio of key business initiatives.
Major Responsibilities Include
- Translate and interpret complex and interrelated datasets and correlating information into predictive forecasts and/or fact-based trend analysis.
- Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions, increasing productivity, or improving sales performance.
- Analyze historical data to identify trends and support decision making.
- Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
- Provide requirements to develop analytic capabilities, platforms, and pipelines.
- Apply statistical or machine learning knowledge to specific business problems and data.
- Formalize assumptions about how users are expected to behave, create statistical definition of the outlier, and develop methods to systematically identify these outliers. Work out why such examples are outliers and define if any actions needed.
- Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes.
- Build decision-making models and propose solution for the business problem you/the team has defined.
- Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
- Utilize code (Python/R/SQL) for data analyzing and modeling algorithms.
- Master’s Degree in Statistics, Applied Mathematics, Operation Research, Economics or a related quantitative field.
- 10+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, Weka, SAS, Matlab)
- Depth and breadth in quantitative knowledge. Excellent quantitative modeling, statistical analysis skills and problem-solving skills. Sophisticated user of statistical tools.
- Experience processing, filtering, and presenting large quantities (Millions to Billions of rows) of data.
- Combination of deep technical skills and business savvy enough to interface with all levels and disciplines across the Commercial organization.
- Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, and ability to accurately determine cause and effect relations.
- PhD Degree in Statistics, Applied Mathematics, Operations.
- Experience articulating business questions and using quantitative techniques to arrive at a solution using available data.
- Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
- Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to both technical and business audiences.
- Demonstrated ability to thrive in ambiguous environments and drive results.
- Strong organizational and multitasking skills with ability to balance competing priorities across global stakeholder groups.
- Experience with Amazon Redshift and other AWS technologies.
- Demonstrated ability to manage a portfolio of projects, resource manage, and develop trusted relationships with business stakeholders.
Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.
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