Senior Data Scientist, Cloud Gaming - Prescriptive Analytics and Optimization
NVIDIA Corporation · Santa Clara, CA
$184,000–$287,500from the description
Jul 15, 2026
Santa Clara, CA
Jul 21, 2026
What this job asks for AI summary
This role sits within a data platform team focused on cloud gaming infrastructure, where the core work involves building and deploying ML, AI, and operations research models for problems like capacity allocation, demand forecasting, real-time scheduling, and user behavior analysis. Day-to-day responsibilities span the full pipeline — from data ingestion and processing at petabyte scale to designing prescriptive optimization solutions using techniques such as linear programming and constraint optimization. It suits a quantitatively strong candidate with substantial hands-on experience in both machine learning and optimization methodologies.
Senior level · 6+ years · Remote · 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
Roughly 18,100 people nationally plausibly meet what this posting asks for (data scientists). range 5,300–27,200
Applicant volume Heavy — This req sits in a large pool with little in its requirements to thin it, and auto-apply tools fire at everything in the occupation. Applying early and leading with the rare skills below is what gets read.
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). 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 sits at the intersection of Data Science and Operations Research — the heavy emphasis on prescriptive analytics, constrained optimization, and linear programming makes 15-2051 (Data Scientists) the best fit, with 15-1299 (Computer Occupations, All Other) as a plausible runner-up given the OR/optimization depth.
Degree requirement is effectively None: the JD states 'BS/MS (or equivalent experience)', explicitly accepting equivalent experience in lieu of a formal degree.
The technology stack (Python, SQL, Delta Lake, Apache Spark, Databricks, MLflow, Grafana, Elasticsearch) is presented as 'Our technology stack relies on…' — a stack narrative section — so those tools are marked preferred rather than hard gates. Python and SQL are separately reinforced by firm language in the requirements block.
Google OR-Tools is listed in the requirements section with 'e.g.' framing, indicating it is the named example of a required class of optimization tooling; it is treated as a hard gate on that capability (with the specific tool being substitutable), consistent with the section-placement rule.
MLflow and Kubeflow appear together under 'Ways to Stand Out from the Crowd' (the preferred/nice-to-have section) and are captured as alternatives of one another.
Time series forecasting is explicitly called 'a plus' under the stand-out section.
The title carries no seniority level word; the title states no level. The 6+ years requirement and scope (real-time production ML/optimization at scale) support a Senior classification.
Compensation range $184,000–$287,500/year is stated explicitly; equity and benefits are also mentioned but not quantified.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): ML/AI modeling.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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