Amazon Sr Data Scientist AWS Enterprise Support Customer Health Insights 

United States, Texas, Austin 

929424801

As part of the CHI team, you'll be responsible for measuring the quality of inputs to CHI, accuracy of measures,and actionability and prioritization of recommendations. You will discover and solve real-world problems by analyzing large amounts of business data, defining new metrics and business cases, designing simulations and experiments, creating models, and collaborating with colleagues. You’ll bring with you a strong quantitative background and thrive in an environment that leverages statistics, machine learning, operations research, econometrics, and business analysis. And in return, you’ll have the chance to work on some of the world’s largest and diverse datasets.Key job responsibilities
• Highly skilled in data and math/stats methods (e.g., scaling, modeling, algorithms). Investigates the feasibility of applying scientific principles and concepts to business problems and products.
• High intellectual curiosity with ability to quickly learn new concepts/frameworks, algorithms and technology
• Analysis of complex datasets to make decisions. Leads scientific research projects. Creates visualizations to drive data insight or describe an end-to-end system. Develops scalable algorithms and models
• Find opportunities to improve relevance and accuracy of CHI-generated recommendations to improve customer health, working closely with Engineering team and business owners
• Demonstrate a high degree of ownership, insist on the highest standards and consistently deliver superior quality results on-time
• Influences multiple teams. Works closely with business teams. Able to build consensus. Advises Sr. Manager/Director.
• Problems are complex to solve. Ability to select an ideal solution from a wide range of data science methodologies
• Takes the lead on large projects, requiring both business and technical domain knowledge expertise. Delivers significant benefit to business.
• Successfully launches data science solutions for the business with minimal assistance. Drives scientific understanding and changes in related systems. Makes technical trade-offs for long term/short-term needs.About the team
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
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- 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
- 4+ years of data scientist 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