Sr. Applied Scientist – AI Velocity Team, Applied AI Acceleration Solutions Architecture

About the role

Are you passionate about using data science to transform how businesses understand and optimize customer interactions at scale? Do you want to build the models and analytics that power the next generation of AI-driven customer experiences while working directly with customers to accelerate production deployments?

Responsibilities

• Design, develop, and deploy statistical models and machine learning pipelines to drive product improvements and business decisions
• Work directly with customers during production pilots to design, build, and deploy AI solutions that demonstrate measurable business value
• Design and execute A/B experiments and causal inference analyses to measure the impact of new features and model changes on customer outcomes
• Build ROI models and business case tools that quantify the value of Connect Customer AI for existing customers transitioning from Connect Customer Basic
• Develop and maintain forecasting systems for demand prediction, capacity planning, and workforce optimization
• Develop and apply NLP and generative AI techniques to extract insights from structured and unstructured data at scale
• Partner with applied scientists and software engineers to productionize models, ensuring reliability, monitoring, and operational excellence
• Enable AI Velocity teams with reusable analytical assets, diagnostic notebooks, and scalable tooling that accelerate customer engagements
• Build benchmarking studies and optimization frameworks that demonstrate value across customer cohorts
• Own success metrics and create mechanisms to measure model performance, adoption, and business impact
• Communicate findings and technical trade-offs to senior leadership and customer executives through written documents (6-pagers, science reviews) and presentations
• Operate as a shared resource across 2-3 AIVT teams simultaneously, providing data science expertise across multiple customer engagements

Qualifications

• Master's degree in engineering, statistics, computer science, mathematics, or a related quantitative field
• 5+ years of quantitative and qualitative data science/business intelligence with significant business impact experience
• 3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
• PhD, or PhD and 4+ years of designing experiments and statistical analysis of results experience
• Experience in A/B testing
• Proficiency in Python and SQL; experience with ML frameworks such as scikit-learn, PyTorch, TensorFlow, or XGBoost
• Track record of delivering end-to-end data science solutions from problem definition through production deployment

Preferred Qualifications

• PhD in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
• Experience with AI/ML technologies
• Knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker
• Experience working directly in customer implementations
• Experience building and managing financial models for business forecasting and problem solving, or experience in Excel (macros, index, conditional list, arrays, pivots, lookups)
• Experience building MLOps workflows (CI/CD for models, feature stores, model registries) or real-time inference systems
• Publishations at peer-reviewed conferences or journals (NeurIPS, ICML, KDD, ACL, EMNLP, etc.)
• Experience with contact center, customer experience, or telecommunications data
• Proven ability to influence without authority and communicate effectively across organizational boundaries

Benefits

Amazon offers comprehensive benefits including health insurance, retirement savings plans, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.