About The Position

WW Amazon Stores Finance Science (ASFS) works to leverage science and economics to drive improved financial results, foster data backed decisions, and embed science within Finance. ASFS is focused on developing products that empower controllership, improve business decisions and financial planning by understanding financial drivers, and innovate science capabilities for efficiency and scale. We are looking for a data scientist to lead high visibility initiatives for forecasting Amazon Stores' financials. You will develop new science-based forecasting methodologies and build scalable models to improve financial decision making and planning for senior leadership up to VP and SVP level. You will build new ML and statistical models from the ground up that aim to transform financial planning for Amazon Stores. We prize creative problem solvers with the ability to draw on an expansive methodological toolkit to transform financial decision-making with science. The ideal candidate combines data-science acumen with strong business judgment. You have versatile modeling skills and are comfortable owning and extracting insights from data. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into business action.

Requirements

  • 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 experience
  • Experience with statistical models e.g. multinomial logistic regression
  • Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
  • Experience managing data pipelines

Nice To Haves

  • Experience as a leader and mentor on a data science team
  • Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
  • Master's degree
  • Experience in forecasting analyses
  • Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage

Responsibilities

  • Demonstrating thorough technical knowledge, effective exploratory data analysis, and model building using industry standard ML models
  • Working with technical and non-technical stakeholders across every step of science project life cycle
  • Collaborating with finance, product, data engineering, and software engineering teams to create production implementations for large-scale ML models
  • Innovating by adapting new modeling techniques and procedures
  • Presenting research results to our internal research community

Benefits

  • health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
  • 401(k) matching
  • paid time off
  • parental leave

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What This Job Offers

Job Type

Full-time

Career Level

Mid Level

Number of Employees

5,001-10,000 employees

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