Head of Data Science/ Machine Learning at HARAMAIN SYSTEMS INC.
Pleasanton, CA
$200,000–$220,000
Jul 23, 2026
Pleasanton, CA
Jul 25, 2026
What this job asks for AI summary
A senior leadership role overseeing data science and machine learning, spanning the full model lifecycle from feature engineering and training through to production deployment and monitoring. The position suits someone with deep hands-on ML engineering ability who has also managed teams building core ML products at high-growth startups, ideally with domain background in fraud, identity verification, or financial risk.
Principal level · 7+ years · Remote · Full-time
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
Roughly 1,200 people nationally plausibly meet what this posting asks for (computer and information systems managers). range 250–1,800
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
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 $178,991 (middle half $141,096–$225,584).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (6)
This is a people-management role ('Head of Data Science/ML') requiring 4+ years managing DS/ML teams, with a leadership round involving the CTO and CEO — mapped to Computer and Information Systems Managers (11-3021). The alt code 15-2051 (Data Scientists) reflects the strong hands-on ML/production-code requirement; the role is a genuine hybrid but management scope is primary.
Location is listed as 'CA/Remote' with no specific city; CBSA is set to Los Angeles-Long Beach-Anaheim as the largest California metro, but the actual base city is unspecified.
Degree requirement: the JD lists Master's/PhD as a target but explicitly states 'exceptional Bachelor's profiles considered' and frames education as preferred — treated as no hard degree gate.
Total experience range is stated as 7–15 years in applied ML/data science; minimum (7) is used for the overall years minimum.
Domain experience in fraud, identity verification, or financial risk is called out as a requirement but names no specific technology or tool, so it is omitted from the skills list per extraction rules.
The end-to-end ML lifecycle items (feature engineering, model training, productionalization, monitoring) are listed as hard requirements in the qualifications block and are retained as concrete technical skills despite being process-oriented, because the JD explicitly gates on them.
Read the full posting
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