PlayStation Global · Los Angeles, CA

Salary
$167,200–$250,800
Posted
Jul 19, 2026
Location
Los Angeles, CA
Last confirmed open
Jul 21, 2026

What this job asks for AI summary

A senior individual-contributor role on a Player Value Science team, focused on building models that quantify player value, measure the incremental impact of product launches and investments, and support long-range financial planning. The work spans causal inference, forecasting, optimization, and machine learning, with close collaboration across Finance, Strategy, and Platform stakeholders. It suits an experienced data scientist comfortable owning ambiguous problems end-to-end and translating complex outputs into commercial decisions.

Senior level · National · Master's required

Must have (7)
PythonSQLPySpark, Dask or Raycausal inferencemachine learningforecastingoptimization
Nice to have (3)
transformersembeddingsexperimentation frameworks

“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

What won't set you apart
Python88%machine learning80%SQL72%

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)

No work location is specified in the posting. Given PlayStation's global footprint and the SBG/PBG Finance Partnership framing (which aligns with PlayStation's UK/European operations), this role is likely based outside the US — the US-based flag has been set to false, but the metro is unknown. Verify the actual office location before benchmarking against US salary data.

The degree requirement states 'typically a Master's or PhD … in operations research, machine learning, statistics, economics, or a related field' under the main requirements block. This has been treated as a hard gate at the Master's level; the word 'typically' introduces some softness, but the phrasing sits firmly in the requirements section.

No overall years-of-experience figure is stated; the JD uses 'proven industry experience' without a numeric floor.

The alt SOC 15-2031 (Operations Research Analysts) is flagged because the role explicitly requires optimization, scenario modelling, and operations-research approaches alongside the ML/statistics work — a genuine occupational ambiguity, though the ML/data-science framing dominates.

Transformers, embeddings, and experimentation frameworks appear under the 'Nice to Have' section and are marked preferred accordingly.

This role's work location reads as outside the US — the candidate pool, comp, and contention benchmarks here are US-only (BLS employment, Adzuna/USAJOBS demand, and certified H-1B wages), so treat them as a rough US reference, not a local market.

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