Amazon · 18 hours ago
Sr. Data Scientist, Special Projects
Seattle, Washington, USA
Full-time
Onsite
Mid, Senior Level
$159K/yr - $215K/yr
3+ years expAmazon.com Services LLC is seeking a Senior Data Scientist for their Special Projects team, focusing on innovative product development. The role involves working with machine learning and advanced analytics to derive insights and enhance customer experiences through collaboration and experimentation.
Artificial Intelligence (AI)DeliveryE-CommerceFoundational AIRetail
Responsibilities
Work hands-on with complex, noisy datasets to derive actionable insights and explain/debug black-box models using interpretability and data-attribution methods
Design and analyze experiments and observational studies with rigorous statistical inference, including confidence intervals, power/sample-size estimation, variance reduction, and appropriate hypothesis testing
Benchmark models and datasets using classical and modern techniques; select ML methods based on data and operational constraints, and evaluate using robust metrics and diagnostic analyses
Apply production-grade measurement and MLOps practices, including data quality monitoring, drift/shift detection, and A/B test design and readouts with disciplined diagnosis of metric movement
Deliver end-to-end analyses that improve team execution and decision-making—define goal-driving metrics with stakeholders, build clear reporting (tables, dashboards, and visualizations), and communicate results that translate into concrete actions
Investigate anomalies and data integrity issues across diverse data sources using structured root-cause analysis, correlation diagnostics, significance testing, and simulation across high- and low-fidelity datasets
Partner closely with cross-functional domain experts to design experiments and interpret results, applying modern statistical methods to evaluate predictive and generative models as well as operational and process performance
Develop production-quality analytics and modeling code—write well-tested, maintainable SQL/Python scripts and analysis workflows that can be promoted into production pipelines, and continuously adopt new statistical methods and best practices as the field evolves
Qualification
Required
Master's degree in computer science, machine learning, engineering, or related fields, or Bachelor's degree and 3+ years of data scientist experience
Experience delivering end-to-end analyses: data cleaning/QC, modeling, evaluation, and stakeholder-ready reporting
Experience with statistical foundation for experiments and inference: confidence intervals, power/sample size, two-sample and permutation tests, sequential testing, and multiple-comparison control
Experience with model evaluation and diagnostics, including ranking/discrimination metrics (e.g., AUROC and precision-recall-gain), probabilistic metrics (e.g., proper scoring rules and divergence-based measures), and calibration assessment (e.g., reliability diagrams, ECE)
Proficient in SQL and Python; able to write production-quality analysis code (testing, version control, reproducible workflows)
Experience working with large-scale data pipelines and production analytics environments (data warehouses/lakes, workflow orchestration, batch or streaming processing)
Preferred
Ph.D. in Computer Science, Engineering, Statistics/Mathematics, Bioinformatics, or a related field
Hands-on experience with model interpretability and black-box debugging (e.g., SHAP/TreeSHAP, Anchors, Integrated Gradients, counterfactuals, influence/data attribution)
Experience with production monitoring and experimentation diagnostics: data quality checks, drift/shift detection (e.g., KS, MMD/embedding drift), and diagnosing metric movement (e.g., instrumentation changes, sample-ratio mismatch, batch effects)
Familiarity with modern deep learning and representation learning, including Transformers and LLM embedding pipelines, with experience in fine-tuning and post-training (e.g., PEFT/LoRA, instruction tuning, preference optimization)
Experience with optimization and simulation to improve operational or experimental processes (e.g., Bayesian optimization, bandits, constrained optimization)
Publications in top ML/AI or statistics venues (conferences/journals) or equivalent evidence of research impact (patents, widely used open-source, internal platforms at scale)
Experience with high-performance or distributed systems (e.g., GPU training, distributed inference) supporting large-scale modeling and experimentation
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
Company
Amazon
Amazon is a tech firm with a focus on e-commerce, cloud computing, digital streaming, and artificial intelligence.
10001+ employees
H1B Sponsorship
Amazon has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (22803)
2024 (21175)
2023 (19057)
2022 (24088)
2021 (12233)
2020 (14881)
Funding
Current Stage
Public CompanyTotal Funding
$8.11BKey Investors
AmazonKleiner Perkins
2023-01-03Post Ipo Debt· $8B
2001-07-24Post Ipo Equity· $100M
1997-05-15IPO
Leadership Team
Douglas J. Herrington
CEO, Worldwide Amazon Stores
Werner Vogels
VP & CTO
Recent News
2026-01-14
2026-01-14
2026-01-14
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