Data Scientist II, Amazon Stores Finance Science

Amazon • Sunnyvale, CA

1d • Onsite

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. This role is for a data scientist to lead high visibility initiatives for forecasting Amazon Stores' financials. The individual 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. The position involves building new ML and statistical models from the ground up that aim to transform financial planning for Amazon Stores. The ideal candidate is a creative problem solver with strong data-science acumen and business judgment, versatile modeling skills, comfortable owning and extracting insights from data, and an excellent communicator.

Requirements

• 2+ years of data scientist experience
• 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
• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
• Experience applying theoretical models in an applied environment
• Bachelor's degree

Nice To Haves

• Experience in a ML or data scientist role with a large technology company
• Experience working on multi-team, cross-disciplinary projects
• Experience effectively communicating complex concepts through written and verbal communication
• Master's degree
• Experience formulating and solving predictive modeling, machine learning, forecasting or statistical modeling problems

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level