Director, Data Science at Jobgether
$215,000–$275,000from the description
Jul 22, 2026
—
Jul 23, 2026
What this job asks for AI summary
A senior leadership role overseeing multiple data science teams building ML systems across consumer search and personalization, delivery logistics, and advertising. Day-to-day work spans setting the machine learning roadmap, hands-on architectural involvement, and partnering with product and engineering to ship models to production. Suited to an experienced ML leader with deep technical grounding who can also operate at the executive level.
Principal level · 8+ years · 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
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). This posting is about at that midpoint.
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 (10)
The role is posted via Jobgether on behalf of an unnamed partner company; the actual employer and specific industry are not disclosed, though the accountabilities reference e-commerce/marketplace/quick-commerce contexts.
Location is stated only as 'United States' with no specific city or metro; CBSA fields are left blank accordingly.
The posting does not explicitly state remote eligibility; it is listed as US-based with no remote language, so remote is set to false.
This role has direct reports, team-building accountability, and executive-level scope across multiple business areas, supporting a Principal (Director-level) seniority classification despite the 8-year minimum experience floor.
The 3+ years of managing data science or engineering teams is a stated requirement but is a role-level gate rather than a named technology, so it is captured in the overall years minimum context rather than as a skill.
Two-tower retrieval systems, contextual bandits, graph neural networks, and causal/uplift modeling are listed together in the Requirements section as a single expertise bullet; each is emitted as a separate required skill.
Databricks and Snowflake appear only under Preferred Qualifications ('platforms such as'), so they are marked preferred.
Streaming feature pipelines and real-time personalization appear under Preferred Qualifications and are marked preferred.
Publications or conference presentations are listed as a preferred qualification but name no concrete technology, so they are omitted per the generic-concept rule.
Ignored 2 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): two-tower retrieval systems, real-time serving systems.
Read the full posting
The employer publishes the full description on their own site — read it there ↗. Or sign in to read it here — it's free, and it also lets you track this application.