Senior Data Scientist - AD/ADAS at Woven by Toyota
Ann Arbor, MI
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Jul 5, 2026
Ann Arbor, MI
Jul 21, 2026
What this job asks for AI summary
A data science engineering role focused on statistical modelling and measurement to shape how a fleet's petabytes of autonomous and non-autonomous vehicle data are acquired, validated, and used for ML training. Day-to-day work involves building evaluation frameworks, identifying rare real-world driving events, and embedding with engineering teams to address domain-specific data challenges in autonomous driving and simulation. Suits applied statisticians comfortable influencing technical strategy across cross-functional teams.
Senior level · 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
Rare in this occupation — lead with these, and say what you built with them.
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 role is titled 'data science engineer' but the core work is applied statistical modeling, evaluation framework development, and data-driven analysis — closer to Data Scientist (15-2051) than Operations Research Analyst (15-2031), though the boundary is genuinely blurry here.
The posting lists no specific location beyond 'US' (the team is distributed across UK, US, and JP). No CBSA or state could be determined.
No total years of experience are stated; seniority is inferred as Senior from the scope: influencing strategic decisions, mentoring others, embedding across engineering teams, and driving org-wide best practices.
NumPy, SciPy, scikit-learn, and pandas are listed as examples under the Python requirement ('e.g. numpy, scipy, scikit, pandas, etc.') within the Minimum Qualifications section — treated as hard gates on those specific libraries since they appear in a required section, though the 'e.g.' framing means other equivalent libraries could substitute.
Statistical analysis and mathematical modelling appear under 'Experience with common data science tools' in Minimum Qualifications and are retained as required skills despite being somewhat generic, because the JD explicitly names them as tools/methods.
ML experience (production ML environment), temporal/sensor data, and AD/ADAS domain experience are all listed under 'Nice to Haves'.
Read the full posting
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