DESCRIPTION
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.
Customer Health Insights, provides field teams with permissions-based data and metrics that quantify their customers AWS cloud health at a glance, and receive prescriptive guidance to maximize the value that customers get from AWS. This personalized experience connects field teams to everything they need to be trusted advisors to AWS customers and partners, and accelerate their cloud journey. CHI brings together data across Sales, Marketing and Global Services, to display a holistic view of customer health across multiple dimensions, along with AI-generated insights and recommendations to help AWS account teams and leadership solve issues, maximize customer value, and accelerate AWS adoption in the most efficient way possible.
As part of the CHI team, you'll be responsible for generating insights that enable AWS leaders to make decisions about their business. You will identify causality between different metrics and outcomes across all metrics and domains within CHI, and potential causality by metrics on the CHI metrics roadmap. You will provide input to metric roadmap prioritisation.
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. Youll 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, youll have the chance to work on some of the worlds 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, hasnt followed a traditional path, or includes alternative experiences, dont let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, its in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, theres nothing we cant achieve in the cloud.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | Austin, TX, USA | Dallas, TX, USA
BASIC QUALIFICATIONS
- 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
PREFERRED QUALIFICATIONS
- 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
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 https://www.amazon.jobs/en/disability/us.
