Data Scientist II, SAnDS

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 have proven analytical capabilities to identify business opportunities, develop predictive models, and optimization algorithms to help us build a 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 platforms, offering over 200 fully featured services from data centers globally. AWS provides services for a broad range of applications including compute, storage, databases, networking, analytics, machine learning, AI, IoT, security, and application development, deployment, and management.

The Global AWS Support BizOps team is looking for a passionate Data Scientist to model contact forecasting, discover insights, and identify opportunities through 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 costs. In this role, you will partner with data engineering, tooling, operations, training, customer service, capacity planning, and finance teams to drive optimization and prediction solutions across the network.

Key job responsibilities

1. 
   
2. Build and manage modeling projects, identify data requirements, and develop methodology and tools grounded in statistics.
   
3. Be an expert in data science, optimization, machine learning, and statistics, and facilitate ideation from concept to execution.
   
4. Work in a customer-obsessed, innovative, and results-oriented manner in a fast-paced, growing organization.
   
5. Embrace ambiguity and collaborate with a highly distributed team of experts.
   
6. Possibly own globally impactful work and grow your career in technical, programmatic, or leadership roles.
   
7. Proficiency in Python or R, or similar modeling languages.
   
8. Apply problem-solving skills, knowledge of data models, and drive results through ambiguity.
   

About the team

We value diverse experiences and encourage candidates to apply even if they do not meet all preferred qualifications. Whether your career is just starting or includes alternative experiences, your unique background is welcome.

Why AWS

AWS is the world’s most comprehensive cloud platform, continuously innovating and trusted by startups to Global 500 companies.

Work/Life Balance

We value work-life harmony and offer flexibility to support your success at work and at home.

Inclusive Team Culture

Our culture of inclusion is fostered through employee-led affinity groups, events, and learning experiences that celebrate diversity.

Mentorship and Career Growth

We provide resources for professional development to help you advance your career and become a well-rounded professional.

- 5+ years of data scientist experience
- 3+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical software (e.g., R, SAS, Matlab)
- 3+ years of experience with machine learning/statistical modeling, data analysis tools, and techniques
- Experience applying theoretical models in an applied environment
- Experience in Python, Perl, or other scripting languages
- Experience in a ML or data scientist role within a large technology company

For workplace accommodations, please visit https://amazon.jobs/content/en/how-we-hire/accommodations.

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