Finding the best job has never been easier
Share
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.Key job responsibilities
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.A day in the life
As a SR. Data Scientistwithin AWS, you will play a key role on the Workforce Planning Science, Tooling and Inspection sub-teams that influence the long-range plans of the business and the technical agenda that supports it. You will influence tools and programs serving senior leaders globally and impacting AWS’ future.
You will lead key analytic initiatives, and mentor junior employees.
The ideal Sr. Data Scientist has a strong sense of ownership, is self-driven, loves breaking new ground. You will bring a mix of experience including complex technical program management, senior stakeholder management, cross-functional collaboration, strategic planning, operational planning, and process improvement.
As a Senior Data Scientistwithin AWS, you will partner across the WFP group . You will play a key role on the Workforce Planning Science, Tooling and Inspection sub-teams that influence the long-range plans of the business and the technical agenda that supports it. You will influence tools and programs serving senior leaders globally and impacting AWS’ future.Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our offices in Seattle and Arlington.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 6+ years of data scientist experience
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Experience with statistical models e.g. multinomial logistic regression
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team
These jobs might be a good fit