Sr Data Scientist, Alexa For Shopping at Amazon
Seattle, WA
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Jul 14, 2026
Seattle, WA
Jul 21, 2026
What this job asks for AI summary
A senior data science role focused on measuring and understanding how customers interact with an AI-powered shopping assistant. The work centers on building customer cohorts, predictive re-engagement models, and scalable metrics frameworks that track adoption and behavior across the shopping lifecycle. The role suits an experienced data scientist comfortable operating in ambiguous, fast-moving product environments and influencing roadmap decisions through rigorous analysis.
Senior level · 4+ years · National · Full-time
“or” means any one of them counts — you don't need all of them.
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
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 Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (6)
The Basic Qualifications gate on '5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab)' — this is a single OR-grouped requirement. SQL is listed as the primary skill with the named alternatives captured accordingly. Python is also separately surfaced as the canonical scripting representative.
The role's overall experience gate is '4+ years of data scientist experience', used as the overall years minimum. The 5-year language/scripting requirement is a per-skill gate.
'Statistical models e.g. multinomial logistic regression' is listed as a hard-required Basic Qualification; it names no single canonical tool, so it is captured as 'statistical modeling' — the specific technique (logistic regression) is illustrative per the JD's own 'e.g.' framing.
Data visualization tools (AWS QuickSight, Tableau, R Shiny) and data pipeline management experience appear under Preferred Qualifications only.
Mentoring and leadership experience is listed under Preferred Qualifications but names no specific technology, so it is omitted from the skills list per extraction rules.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): data pipeline management.
Read the full posting
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