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

Amazon • Seattle, WA

1d • Onsite

About The Position

As a Senior Applied Scientist within the Applied AI Solutions team, you will collaborate across AI Velocity Teams (AIVT), enabling multiple customer engagements simultaneously. You will lead data science initiatives that span the full lifecycle — from identifying high-value business problems and formulating hypotheses, through rigorous experimentation and modeling, to deploying production-grade solutions that serve thousands of customers. You will bring deep expertise in statistical inference, machine learning, and experimental design to drive measurable impact across Amazon Connect's analytics products and broader Connect AI initiatives. A critical dimension of this role is working directly with customers during production pilots to accelerate time-to-value. You will partner with Applied AI Solutions Architects and Customer Success Specialists to design, build, and deploy AI solutions in customer environments during fixed deployment cycles. You will enable field teams with data-driven insights, reusable analytical assets, ROI tools, and scalable tooling that accelerate customer engagements and solution delivery. Your work will directly influence customer decisions to adopt Connect Customer AI by quantifying business outcomes and demonstrating measurable value. You will operate with significant autonomy, owning the scientific direction of your projects while collaborating with applied scientists, software engineers, product managers, technical, and business stakeholders. You will be expected to identify the right methodology for each problem — whether that's a classical statistical approach, a modern deep learning technique, or a novel combination — and communicate your findings clearly to both technical and non-technical audiences. This role spans Connect AI initiatives including conversational analytics and agentic AI capabilities, offering the opportunity to pioneer data science approaches that scale intelligent analytics worldwide.

Requirements

• 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

Nice To Haves

• 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
• Publications 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

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

Benefits

• sign-on payments
• restricted stock units (RSUs)
• 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: Senior