Data Scientist II, Operations Technology Solutions, Global Workforce Management
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Job Location:
Nashville, IN - USA
Monthly Salary:
Not Disclosed
Posted on:
18 hours ago
Vacancies:
1 Vacancy
Job Summary
Join Amazons Global Workforce Management team as a Data Scientist II and Model Enhancement Specialist where youll develop and validate advanced forecasting models that optimize staffing for one of the worlds largest operations this role youll apply cutting-edge machine learning and statistical modeling techniques to solve complex workforce optimization challenges across global regions. This position offers the opportunity to drive technical innovation in workforce analytics collaborate with cross-functional data teams and directly impact strategic planning decisions for Operations Technology Solutions.
Key job responsibilities
- Validate and enhance forecasting models while developing specialized workforce analytics for field operations
- Create advanced scenario modeling algorithms and support model expansion to new organizations with technical expertise
- Collaborate with data teams to develop validation frameworks and establish technical metrics for model performance
- Design and implement specialized forecasting components with clear performance metrics and implementation paths
- Drive technical innovation in workforce analytics and mentor junior team members on advanced analytical approaches
- Travel up to 10% to support model implementation and stakeholder collaboration
A day in the life
As the Model Enhancement Specialist youll begin your day reviewing model performance metrics and validation results across multiple workforce forecasting systems. Youll collaborate with data engineering teams to refine algorithms then work with business stakeholders to translate complex technical concepts into actionable insights. Your afternoons might involve developing new scenario modeling approaches in Python or R conducting statistical analysis to improve forecast accuracy or presenting technical findings to OTS Leadership. Youll regularly work with cross-functional teams to integrate analytical solutions validate model outputs against real-world outcomes and identify opportunities for technical innovation in workforce optimization.
About the team
The Global Workforce Management (GWM) team is at the forefront of applying advanced analytics and machine learning to workforce optimization at Amazon. We develop and maintain sophisticated data-driven forecasting models that predict demand volume and staffing scenarios for Operations Technology Solutions (OTS) and expanding organizations across global regions. Our work directly enables strategic planning and operational decisions that impact millions of customer orders. The team values technical excellence innovation in analytical methodologies and collaborative problem-solving. Were expanding our modeling capabilities to new business units and exploring cutting-edge approaches in AI and machine learning making this an exciting time to join and shape the future of workforce analytics at Amazon.
- 2 years of data scientist experience
- 3 years of data querying languages (e.g. SQL) scripting languages (e.g. Python) or statistical/mathematical software (e.g. R SAS Matlab etc.) experience
- 3 years of machine learning/statistical modeling data analysis tools and techniques and parameters that affect their performance experience
- 1 years of guiding and coaching a group of researchers experience
- 1 years of working with or evaluating AI systems experience
- 1 years of creating or contributing to mathematical textbooks research papers or educational content experience
- Masters degree in Science Technology Engineering or Mathematics (STEM) or experience working in Science Technology Engineering or Mathematics (STEM)
- Experience applying theoretical models in an applied environment
- Ph.D. in Science Technology Engineering or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python Perl or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience working on multi-team cross-disciplinary projects
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Key job responsibilities
- Validate and enhance forecasting models while developing specialized workforce analytics for field operations
- Create advanced scenario modeling algorithms and support model expansion to new organizations with technical expertise
- Collaborate with data teams to develop validation frameworks and establish technical metrics for model performance
- Design and implement specialized forecasting components with clear performance metrics and implementation paths
- Drive technical innovation in workforce analytics and mentor junior team members on advanced analytical approaches
- Travel up to 10% to support model implementation and stakeholder collaboration
A day in the life
As the Model Enhancement Specialist youll begin your day reviewing model performance metrics and validation results across multiple workforce forecasting systems. Youll collaborate with data engineering teams to refine algorithms then work with business stakeholders to translate complex technical concepts into actionable insights. Your afternoons might involve developing new scenario modeling approaches in Python or R conducting statistical analysis to improve forecast accuracy or presenting technical findings to OTS Leadership. Youll regularly work with cross-functional teams to integrate analytical solutions validate model outputs against real-world outcomes and identify opportunities for technical innovation in workforce optimization.
About the team
The Global Workforce Management (GWM) team is at the forefront of applying advanced analytics and machine learning to workforce optimization at Amazon. We develop and maintain sophisticated data-driven forecasting models that predict demand volume and staffing scenarios for Operations Technology Solutions (OTS) and expanding organizations across global regions. Our work directly enables strategic planning and operational decisions that impact millions of customer orders. The team values technical excellence innovation in analytical methodologies and collaborative problem-solving. Were expanding our modeling capabilities to new business units and exploring cutting-edge approaches in AI and machine learning making this an exciting time to join and shape the future of workforce analytics at Amazon.
- 2 years of data scientist experience
- 3 years of data querying languages (e.g. SQL) scripting languages (e.g. Python) or statistical/mathematical software (e.g. R SAS Matlab etc.) experience
- 3 years of machine learning/statistical modeling data analysis tools and techniques and parameters that affect their performance experience
- 1 years of guiding and coaching a group of researchers experience
- 1 years of working with or evaluating AI systems experience
- 1 years of creating or contributing to mathematical textbooks research papers or educational content experience
- Masters degree in Science Technology Engineering or Mathematics (STEM) or experience working in Science Technology Engineering or Mathematics (STEM)
- Experience applying theoretical models in an applied environment
- Ph.D. in Science Technology Engineering or Mathematics (STEM)
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in Python Perl or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience working on multi-team cross-disciplinary projects
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at TN Nashville - 132500.00 - 179200.00 USD annually
USA TX Austin - 136000.00 - 184000.00 USD annually
Required Experience:
IC
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
About Company
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