Senior Data Scientist

Location: Bellevue, WA

*** Mention DataYoshi when applying ***

  • Bachelor's Degree
  • 5+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
  • 4+ years working as a Data Scientist
  • Strong verbal and written communication skills and an ability to work in a team environment
  • 4+ years work experience as a data scientist with associated modelling and analytics experience
Internal Audit’s mission is to help our businesses improve controllership, operational efficiency, and customer experience.
Are you passionate about data, enjoy solving complex analytical problems, building predictive and descriptive analytics to derive insight at scale - all in a challenging, fast-paced environment?

Internal Audit is seeking a seasoned Senior Data Scientist leader to accelerate the growth of Amazon Internal Audit’s Data Science & Risk Informatics initiatives. You will architect and execute a research roadmap that connects risk to the business, which will enable the construction of inference models to aid data driven Risk Assessment across all of Amazon. This role will also be occasionally be solicited to consult on audit engagements to assess the best approach on auditing existing ML models or where Data Science methodologies can be leveraged to gain better insights to generating recommendations that address a range of problems across the entire company.

The ideal candidate will be an established expert in data science and have excellent communication skills to work closely with stakeholders to translate business needs into methodology and data-driven findings into actionable insights. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and ability to work in a dynamic environment able to support the needs of different businesses

Roles and Responsibilities
  • Work with business teams, engineers and leadership to identify and prioritize customer and business problems
  • Translate problems into specific analytical questions and form hypotheses that can be answered with available data using statistical methods or identify additional data needed in core datasets to fill any gaps
  • Coach others on the team with a systematic peer review and & model proposal evaluation
  • Perform hands-on data analyses and modeling with big data to develop insights and recommendations to inform decisions across the program
  • Propose methods of summarizing insights from large text using natural language processing techniques
  • Design and run A/B experiments to validate the hypotheses and evaluate the impact of your optimizations and communicate your results to various stakeholders
  • Collaborate with engineers and product managers to build scalable solutions and new capabilities
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, visit

This role can be based in Bellevue WA, Arlington VA, or near any Amazon Corporate Office.

  • Master’s degree (or Bachelor's degree + 8 years of experience) in a quantitative discipline such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science.
  • Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations.
  • Experience with AWS technologies like Redshift, SageMaker, EC2, Lambda, & EMR.
  • Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
  • Combination of deep technical skills and business acumen enough to interface with all levels and disciplines within our organization.

*** Mention DataYoshi when applying ***

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