Sr. Data Scientist, Special Projects
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Job Location:
Seattle, OR - USA
Monthly Salary:
Not Disclosed
Posted on:
3 hours ago
Vacancies:
1 Vacancy
Job Summary
As a Data Scientist you will be working at the intersection of machine learning and advanced analytics you will help develop innovative products that enhance customer experiences. Our team values intellectual curiosity while maintaining sharp focus on bringing products to market. Successful candidates demonstrate responsiveness adaptability and thrive in our open collaborative entrepreneurial environment.
Working at the forefront of both academic and applied research you will join a diverse team of scientists engineers and product managers to solve complex business and technology problems using scientific approaches. You will collaborate closely with other teams to implement innovative solutions and drive improvements.
Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive flexible and able to succeed within an open collaborative entrepreneurial startup-like environment. At the forefront of both academic and applied research in this product area you have the opportunity to work together with a diverse and talented team of scientists engineers and product managers and collaborate with other teams.
Key job 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-makingdefine 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 codewrite 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.
A day in the life
New data has just landed and promoted to our datalake. You load the data and verify its overall integrity by visualizing variation across target subsets. You realize we may have made progress toward our goals and begin to test the validity of your nominal results. At midday you grab lunch with new coworkers and learn about their fields or weird interests (there are many). You generate visualizations for the entire dataset and perform significance tests that reinforce specific findings. You meet with peers in the afternoon to discuss your findings and breakdown the remaining tasks to finalize your group report!
About the team
Innovators wanted! Are you an entrepreneur A builder A dreamer This role is part of an Amazon Special Projects team that takes the companys Think Big leadership principle to the limits. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If youre interested in innovating at scale to address big challenges in the world this is the team for you.
- Masters degree in computer science machine learning engineering or related fields or Bachelors 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).
- 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.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Working at the forefront of both academic and applied research you will join a diverse team of scientists engineers and product managers to solve complex business and technology problems using scientific approaches. You will collaborate closely with other teams to implement innovative solutions and drive improvements.
Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive flexible and able to succeed within an open collaborative entrepreneurial startup-like environment. At the forefront of both academic and applied research in this product area you have the opportunity to work together with a diverse and talented team of scientists engineers and product managers and collaborate with other teams.
Key job 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-makingdefine 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 codewrite 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.
A day in the life
New data has just landed and promoted to our datalake. You load the data and verify its overall integrity by visualizing variation across target subsets. You realize we may have made progress toward our goals and begin to test the validity of your nominal results. At midday you grab lunch with new coworkers and learn about their fields or weird interests (there are many). You generate visualizations for the entire dataset and perform significance tests that reinforce specific findings. You meet with peers in the afternoon to discuss your findings and breakdown the remaining tasks to finalize your group report!
About the team
Innovators wanted! Are you an entrepreneur A builder A dreamer This role is part of an Amazon Special Projects team that takes the companys Think Big leadership principle to the limits. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If youre interested in innovating at scale to address big challenges in the world this is the team for you.
- Masters degree in computer science machine learning engineering or related fields or Bachelors 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).
- 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.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including 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 and parental leave. Learn more about our benefits at WA Seattle - 159200.00 - 215300.00 USD annually
Required Experience:
Senior IC
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
About Company
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