Apply statistical techniques, machine learning, and data analysis to solve well‑defined business problems and deliver measurable improvements.
Compensation
USA, WA, Bellevue - 108,300.00 - 160,000.00 USD annually
Responsibilities
Use statistical methods, machine learning algorithms, and data analysis techniques to translate well‑defined business problems into data science solutions that improve processes and systems.
Gather, clean, and integrate large datasets from multiple sources to build and validate models, ensuring data integrity and adherence to best practices throughout the pipeline.
Design and deliver metrics, visualizations, and reports that compare results against benchmarks and original project goals, enabling clear and informed decision‑making for stakeholders.
Collaborate with business, science, and engineering teams to understand customer needs, identify opportunities, and develop scalable analytical solutions using tools such as Python, R, or SQL.
Evaluate opportunities to integrate generative artificial intelligence tools into workflows, refining outputs and applying responsible practices to augment productivity and solution quality.
Requirements
Master's degree in Science, Technology, Engineering, or Mathematics (STEM)
Nice to have: Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
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)
Hands-on Data Engineer focused on building complex SQL Server systems across Linux and Windows environments, utilizing PowerShell, APIs, Python, and AI/LLM technologies.
Responsibilities
Design, build, and optimize complex SQL Server solutions, emphasizing performance tuning, indexing, and data modeling.
Manage relational and semi-structured data, including JSON stored in SQL Server and multi-dimensional datasets.
Query and transform JSON using native SQL Server tools, such as OPENJSON and JSON_VALUE.
Use PowerShell, SQL Server tools, and scripting to automate processes.
Enhance functionalities by integrating with APIs and external systems.
Lead high-impact data science initiatives across marketing, growth, and product, defining strategy, building models, and translating insights into recommendations.
Locations (2)
San Diego, California, United States
San Francisco, California, United States
Compensation
The annual U.S. salary range for this full-time position is $179,500 - $269,500.
Responsibilities
Lead high-impact data science initiatives across marketing, growth, and product, from problem definition through methodology, execution, interpretation, and recommendation.
Define org-level technical strategy, identify high-leverage opportunities, and establish best practices for experimentation, causal measurement, modeling, AI-assisted development, and decision science.
Design, analyze, and interpret experiments and quasi-experiments; build scalable frameworks to estimate incrementality, treatment effects, and long-term business value.
Develop ML, uplift, heterogeneous treatment effect, and adaptive experimentation models to improve targeting, segmentation, personalization, lifecycle optimization, audience strategy, budget allocation, and product decisions.
Build and maintain backend services and APIs that power ML-driven features across the Good Inside platform, integrating and orchestrating ML models and third-party APIs into production systems.
Compensation
base salary for this role will be $205k - $235k
Responsibilities
Design, build, and maintain backend services and APIs that power ML-driven features across the Good Inside platform
Integrate and orchestrate ML models and third-party ML APIs into production systems
Build data pipelines and infrastructure to support model serving, feature storage, and real-time personalization
Collaborate closely with product, mobile, and design teams to translate ML capabilities into user-facing features
Own the reliability, performance, and scalability of ML-adjacent backend systems
Requirements
Computer Science degree or equivalent
Nice to have: LLM Application Development
Nice to have: Infrastructure & DevOps Fluency (CI/CD, monitoring, observability)
Nice to have: recommendation systems, personalization engines, content ranking algorithms
Lead manufacturing engineering for AWS Board Core Design team, driving test system development, qualification, and continuous improvement across global manufacturing sites.
Locations (3)
Austin, Texas, United States
Seattle, Washington, United States
Cupertino, California, United States
Compensation
USA, CA, Cupertino - 183,000.00 - 247,600.00 USD annually
USA, TX, Austin - 159,200.00 - 215,300.00 USD annually
USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually
Responsibilities
Develop, deploy, qualify, and continuously improve test systems and processes at manufacturing sites
Perform PCBA debug and root-cause failure analysis
Create runbooks and train technicians and operators
Support recurring certification programs
Analyze failure data to identify trends and recommend improvements
Partner with Marketing, Growth, Sales, Finance, and Product to evaluate acquisition, retention, ROI, user journeys, funnels, marketplace dynamics, donation conversion, and engagement.
Requirements
Master’s degree or Ph.D. in a quantitative field, or equivalent applied experience coupled with a bachelor’s degree
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