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Senior Data Scientist, AWS Workforce Planning

Job ID: 2503859 | Services LLC


Success in any organization begins with its people and having a comprehensive understanding of our workforce and how we best utilize their unique skills and experience is paramount to our future success.
AWS is looking for an exceptional Senior Data Scientist with ML expertise to join the Workforce Planning team.
This Senior Data Scientist has proficiency in employing workforce and human behavior insights, operations research and machine learning techniques to build models and algorithms that enable the acceleration of revenue growth, improved operational efficiencies & delivery. Ultimately, results will be delivered through a workforce plan of optimized size and level in service of predictably accelerating product innovation, and enhancing the customer experience. Moreover, this Senior Data Scientist will work in partnership with the core WFP team that requires thought leadership to advance WFP content across AWS. This individual has proficiency in employing workforce and human behavior insights, strong business operations fundamentals and good judgement.
In this role, you will be responsible for using operational and human capital data and leveraging machine learning methods to map enterprise strategies into actionable delivery plans, guiding data driven business decisions that results in predicting outcomes, understanding complex data relationships, and developing a quantitative return on investment. You will work closely with the business and technology teams.
The ideal Senior Data Scientist has a strong sense of ownership, is self-driven, loves breaking new ground. You will bring a mix of experience including complex program management, cross-functional collaboration, strategic thinking, technical expertise, and process improvement. If you enjoy working in a fast-paced dynamic environment and being challenged by new problems, we’d like to speak with you!

Key job responsibilities
Strategic Analytics & Consultative Guidance:
o Develop the next generation of Workforce ML Predictive Analytics & Forecasting models providing simulations, what-if analytics, and prescriptive analytics functionality
o Determine the correct usage of core modelling techniques, and their applicability to the available data and use cases of the Workforce Planning team
o Facilitate business case development and prioritization of opportunities based on ROI & feasibility assessment.
o Provide business executives and stakeholders with thought-leadership and insights to enable continuous improvement across key financial, performance, and consumer metrics.
o Partner with key stakeholders to create accurate financial forecasts and identify key drivers impacting performance versus benchmarks
o Directly work alongside Data Science team to scope and develop advanced autonomous Machine Learning systems to further improved existing forecasting and prediction capabilities within WFP
o Present critical information in a format that is immediately useful to answer questions about the inputs and outputs of Forecasting systems and improving their performance.

Project Management: Manage analytical projects by leveraging agile methodologies to partner across business functions, meet deliverables, and actively champion solution adoption across the business.

Requirements Gathering: Conduct interviews with key business stakeholders to translate business objectives into analytical project deliverables to realize business goals.

Data Preparation: Write high quality code and organize data structures to efficiently drive scalable workflows and analyze data.

Data Governance: Develop, maintain and perform processes to continuously monitor data quality and integrity

We are open to hiring candidates to work out of one of the following locations:

Seattle, WA, USA


- MS degree in Business, Economics, Statistics, Data Science, Data Mining, or other quantitative field
- 6+ years of experience in Analytics, Data Science, Business Intelligence or other quantitative disciplines and a degree in statistics, economics, mathematics, engineering, or similar quantitative discipline
- Demonstrated experience developing successful analytics-based solutions to business problems
- Familiarity with probability, probability distributions, statistics and causal inference, applied time series or knowledge of various machine learning techniques and key parameters that affect their performance and experience bringing machine learning models from proof of concept through production release
- 5+ Experience with data scripting languages (e.g. SQL, Python) or statistical/mathematical software (e.g. R, SAS, or Matlab)
- Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research teams, engineering teams and business audiences.


- Ability to work cross-functionally and with others with diverse skill sets
- Ph.D. in Science, Engineering, Economics, Statistics or other quantitative fields
- Knowledge of data warehouse and AWS services
- Experience working with workforce planning data

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

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit Applicants should apply via our internal or external career site.