About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Research Services.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

You will help drive data-driven solutions across North American operations by designing, building, and deploying forecasting, causal, and optimization models that inform operational decision-making.

• Interface with stakeholders to translate business problems into technical designs and measurable outcomes
• Build machine learning, optimization, and causal-inference models targeted at operations problems
• Source, clean, and analyze large, complex datasets from warehouse and logistics systems
• Leverage generative AI and other AI-based tools to accelerate model development and explain model outcomes
• Own projects end-to-end: scoping, stakeholder engagement, data enablement, model development, and handoff to production teams

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A Day in the Life

You’ll be a single-threaded owner for projects within North American Operations, working directly with partner teams across Operations and Finance. Expect to alternate between code and analysis, design documents and stakeholder meetings, and communicating results to both technical and non-technical audiences.

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About the Team

You will join a cross-functional team of Data Scientists, Applied Scientists, and Economists who deliver analytics and decision tools used across the operations network. The team values clear problem framing, deep quantitative analysis, and concise communication to influence decisions at all levels.

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Basic Qualifications

• 1+ years experience with data querying languages (e.g., SQL), scripting (e.g., Python) or statistical software (e.g., R, SAS, Matlab)
• 2+ years experience as a data/research scientist, statistician, or quantitative analyst working with large, complex data sources (internet-based or operations-heavy environments)
• Master’s degree in a STEM field (Science, Technology, Engineering, Mathematics) or equivalent practical experience

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Preferred Qualifications

• Ph.D. in a STEM field
• Strong knowledge of machine learning concepts and practical application to reasoning and problem solving
• Experience working with or evaluating AI systems, including generative AI tools
• Demonstrated ability to apply quantitative analysis to business problems and support data-driven decisions
• Excellent written and verbal communication skills; ability to present complex analyses clearly

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Compensation & Benefits

• Base salary range (Bellevue, WA): USD 108,300 — USD 160,000 per year
• Total compensation may include sign-on payments, equity or other long-term incentives, and will be determined by experience, qualifications, and location
• Comprehensive benefits typically include medical/dental/vision, retirement/401(k) options, paid time off, parental leave, and other standard employee benefits

If you require an accommodation during the application or hiring process, please contact the recruiting partner assigned to this role.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.