Redmond, WA

Salary
—
Posted
Aug 14, 2026
Location
Redmond, WA
Last confirmed open
Sep 24, 2026

What this job asks for AI summary

This role builds end-to-end predictive and econometric/ML models in Python to support demand forecasting and supply operations decision-making. The data scientist works closely with program managers and stakeholders to translate business requirements into scalable analytical solutions, and contributes to a Data Science Center of Excellence by promoting best practices in tools like Power BI and AI-assisted development.

Mid level · 2+ years

Must have (4)
PythonMachine learningStatistical analysisForecasting models
Nice to have (2)
Power BIAI copilots

Posted 2 times — it's one opening, so apply once.

We read this from the posting text with AI. Skim the description below before ruling yourself out.

How this req sits in the market our data

What won't set you apart
Python88%Machine learning80%Statistical analysis60%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $122,874 (middle half $87,544–$162,374).

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Aug 15, 2026. It is a model, not a headcount.

Why we read it this way (6)

The posting lists a security screening mention alongside degree requirements but does not specify a formal US government clearance level or gate on holding one — treated as no clearance requirement.

The degree requirement accepts equivalent experience in lieu of any formal degree, so the degree requirement is set to None.

The minimum experience threshold is 2 years (Bachelor's + 2 years), which is the lowest qualifying path stated.

Power BI and AI copilots appear in narrative/responsibility context rather than a formal requirements block, so they are marked as preferred.

The role sits at the boundary between Data Scientists (15-2051) and Operations Research Analysts (15-2031) due to its dual emphasis on ML/statistical modeling and demand/supply operations forecasting.

Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): Econometric modeling.

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