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Data Scientist, AWS Support Strategy Analytics and Data Science, Support Engineering
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Do you have proven analytical capabilities to identify business opportunities, develop predictive models and optimization algorithms to help us build state of the art Support organization?
At Amazon, we are working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We set big goals and are looking for people who can help us reach and exceed them. Amazon Web Services (AWS) is one of the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Amazon Web Services, Inc. provides services for broad range of applications including compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), security, and application development, deployment, and management.
Global AWS Support BizOPs team is looking for a Data Scientist to model contact forecasting, discovering insights and identifying opportunities through the use of statistics, machine learning, and deep learning to drive business and operational improvements. A successful candidate must be passionate about building solutions that will help drive a more efficient operations network and optimize cost. In this role, you will partner with data engineering, Tooling team, operations, Training, Customer Service, Capacity planning and finance teams, driving optimization and prediction solutions across the network.
Key job responsibilities
We are looking for an experienced and motivated Data Scientist with proven abilities to build and manage modeling projects, identify data requirements, build methodology and tools that are statistically grounded
The candidate will be an expert in the areas of data science, optimization, machine learning and statistics, and is comfortable facilitating ideation and working from concept through execution.
The candidate is customer obsessed, innovative, independent, results-oriented and enjoys working in a fast-paced growing organization.
An interest in operations, manufacturing or process improvement is helpful. The ability to embrace this ambiguity and work with a highly distributed team of experts is critical.
While this is a small team, there is opportunity to own globally impactful work and grow your career in technical, programmatic or people leadership.
You will likely work with Python or R, though specific particular modelling language.
Your problem-solving ability, knowledge of data models and ability to drive results through ambiguity are more important to us.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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.
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 & 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
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.
BASIC QUALIFICATIONS
- 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- Knowledge of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
- Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
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
