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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? 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.
Job Responsibility
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
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 have
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
What we offer
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)