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. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

Do you share a passion to make customers successful? Do you believe that a deep understanding of customer and business priorities can transform an organization? Are you excited to discover and solve thorny business challenges through data science and advanced analytics solutions? Do you thrive in a dynamic environment working with diverse teams cutting across functions, organizations, and cultures to achieve a common goal?

Amazon Web Services (AWS) is a dynamic and rapidly growing business within Amazon and the leader in providing secure, reliable, scalable, and innovative services that help over a million businesses, governments, education, and not for profits across the globe scale and grow! AWS provides a wide set of scalable services to meet customer needs.

The AWS Global Deal Strategy and Programs (GDSP) organization is responsible for the Private Pricing Program. The Private Pricing Analytics and Insights (PPA&I) team owns building scalable analytical solutions that enable the GDSP organization with actionable insights to make data-driven decisions. This role will focus on Data Science, and Analytics related to the Private Pricing Program, requiring deep technical skills, strong business acumen and a deep analytical background to provide actionable data-driven insights and decision support. As a member of this team, you will dive deep into our data and harness your strong data extraction, transformation, and load (ETL) skills to create data structures, build machine learning models, create forecasting , predictive and prescriptive models, build dashboards and visualization to support business strategy and enable GDSP to achieve its goals.

The individual must have the ability to communicate effectively across multiple technical and non-technical business units, as well as across other geographies. Successful members of this team collaborate effectively to solve data problems, are highly organized and detail-oriented, implement new solutions for complex problems, and deliver successfully against highest standards. The ideal candidate will be a highly motivated individual that seeks to “tell the story” of the data with little direction or supervision.

Key job responsibilities
Key responsibilities include, but are not limited to:
• Support the development of continuously-evolving business analytics and data models, own the quantitative analysis of the performance of our sales team, customers, deal team, partners, markets, and products/services in context of private pricing.
• Use machine learning, data mining, statistical techniques and run A/B experiments to solve complex business problems.
• Perform hand-on analysis and modeling of large datasets to develop actionable insights
• Design, develop and evaluate highly innovative models for predictive learning.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
• Develop a deep understanding of sales metrics, reporting tools, and data structures in order to identify and drive resolution of issues, provide actionable intelligence with existing metrics or identify, develop, and propose new metrics, dashboards, scorecards or new tools.
• Develop relationships and processes with sales, finance, sales operations, and other functional teams to identify and address reporting issues.
• Manage and develop advanced analytical tools that align, and simplify, monthly business reviews, annual planning, and forecasting processes.
• Create operational templates and processes to compile and standardize disparate information that drive standardized reporting and metrics tracking.
• Generate ad-hoc and monthly operational analysis and reports, based on the needs of the stakeholders.

About the team
Diverse Experiences
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.

Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

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, there’s nothing we can’t achieve in the cloud.

Inclusive Team Culture
Here at AWS, it’s 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 and 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.

BASIC QUALIFICATIONS

- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 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 or similar role involving data extraction, analysis, statistical modeling and communication experience
- Experience with statistical models e.g. multinomial logistic regression

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
- Experience documenting modeling for technical and business leaders
- Experience working with data engineers and business intelligence engineers collaboratively
- Demonstrated expertise in AI/ML, forecasting, predictive models, classification, clustering and other advanced data science applications.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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