Data Scientist, SAMBA

Amazon • Newark, NJ

11d

About The Position

We are seeking a Data Scientist to own our causal inference infrastructure and drive sophisticated modeling that measures the incremental impact of business decisions. This role requires deep expertise in advanced causal inference methodologies—including synthetic control methods, Synthetic Difference-in-Differences (SDID), and Bayesian approaches—to design rigorous experiments, estimate long-term customer behavior effects, and translate complex analytical results into clear business recommendations. You will own the development and continuous improvement of these causal inference models while being responsible for machine learning operations at scale to ensure our organization makes data-driven decisions with confidence.

At Audible, you will have an opportunity to make the best of your skillsets to both develop advanced scientific solutions and drive critical customer and business impact. You will play a key role to drive end-to-end solutions from understanding our business and business requirements, identifying opportunities from a large amount of historical data and engaging in research to solve the business problems. You'll seek to create value for both stakeholders and customers and inform findings in a clear, actionable way to managers and senior leaders. You will be at the heart of an agile and growing area at Audible.

Requirements

• 2+ years of building machine learning models or developing algorithms for business application experience
• Experience in experimental design, causal inference, and statistical analysis
• Experience with statistical power analysis, sampling design, and bias/variance tradeoffs
• Experience contributing to scalable, production-quality code
• Master's degree in Statistics, Economics, Mathematics, or related quantitative field
• Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. Python, R, Stata, Matlab, etc.)

Nice To Haves

• Ph.D. in Statistics, Economics, or related quantitative field with strong technical implementation focus
• Experience contributing to end-to-end technical infrastructure for experimentation or modeling systems
• Deep understanding of causal inference methodologies and challenges
• Familiarity with modeling techniques used to estimate long-term effects from short-term data
• Track record of translating complex statistical models into production systems
• Problem-solving mentality with demonstrated curiosity and ability to ask clarifying questions
• Experience in consumer technology or subscription-based business models
• Ability to balance sophisticated modeling discussions with hands-on technical implementation
• Experience with containerization technologies and cloud infrastructure (AWS preferred)

Responsibilities

• Design and execute geo-level randomized experiments to measure incremental impact
• Apply statistical techniques to evaluate causal impact in quasi-experimental settings
• Ensure experiments are statistically valid by evaluating sampling strategies, statistical power, and potential sources of bias
• Develop models that estimate long-term effects from short-term experiments using machine learning
• Estimate how changes in customer behavior persist and decay over time
• Own and maintain the geo-testing codebase, including deployment and scalability
• Implement machine learning models at scale with focus on performance optimization
• Partner with stakeholders to ensure models align with real business dynamics
• Engage deeply with business problems through curiosity-driven questioning and brainstorming
• Translate experimental results into financial impact and investment recommendations
• Analyze marginal and average revenue impacts relative to costs
• Communicate complex quantitative ideas clearly to non-technical stakeholders
• Demonstrate understanding of Audible's business model and customer experience

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