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Welcome to SVA’s jobs portal, your one-stop shop for finding the most up to date source of employment opportunities. We have partnered with the National Labor Exchange to provide you this information. You may be looking for part-time employment to supplement your income while you are in school. You might be looking for an internship to add experience to your resume. And you may be completing your training ready to start a new career. This site has all of those types of jobs.

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Amazon Data Science Manager, Managed Engineering and Data Science (MOEDS) in Herndon, Virginia

Description

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services.

We are in search of an experienced Software Developer to develop products for our customers to enable AWS to expand its global footprint. Developers at Amazon work on real world problems on a global scale, own systems end-to-end, and influence the direction of our technology that impacts hundreds of millions of customers around the world

Key job responsibilities

  • Manages a team of scientists and engineers.

  • Leads a team of scientists working to solve Managed Operations business problems. You also work with the customers to scope scientific projects and evaluate artifacts/solutions to ensure they meet business needs.

  • Effectively hires, coaches, and promotes team members.

  • Manages complex science problems and tooling efforts, decisions, and escalations. Mitigates long-term risks.

  • Regularly review key performance metrics, to ensure the team's efforts align with overarching business objectives, fostering a results-driven environment.

  • Cross-departmental collaboration is key, you will strengthen relationships with other teams, streamlining processes for optimal deliveries.

About the team

The Managed Operations Data Science (MODS) team’s mission is to harness the power of science to uncover truth, trends, and patterns to enhance operational efficiencies, identify toil, optimize staffing strategies, and improve experience of our operators across AWS. We provide scientific insights to steer business strategies and engineering solutions in AWS resulting in tangible cost savings, streamlines processes, and optimized operational performances, thus driving measurable impact in teams’ operations. In 2023, we debuted two analytical products- Golden Ether and Ember to improve operational efficiency and shape workforce of Amazon Dedicated Cloud (ADC) teams. We are now expanding the scope of our analytics and dashboards to all of AWS with AWS Ether including commercial, GovCloud, and digital sovereign regions.

Our team is driven by a shared vision of achieving operational excellence through data analytics and Machine Learning (ML). We are primarily composed of data scientists and engineers. Our scientists deliver research and actionable insights on operational efficiency and effectiveness by providing measurements and proactive recommendations on operations and operator experience. Our engineers ingest, process, and maintain data to aide in analytics for our team and other analytical teams across AWS. Working together, we recommend data driven strategies to improve operational posture, reduce service outages, reduce human effort, improve issue detection, and improve operational safety and service reliability for all of AWS.

Basic Qualifications

  • 5+ years of building quantitative solutions as a scientist or science manager experience

  • 2+ years of scientists or machine learning engineers management experience

  • 5+ years of applying statistical models for large-scale application and building automated analytical systems experience

Preferred Qualifications

  • Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)

  • Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems

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.

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