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Currently available for select engagements

Hire Data Analyst for Game Studios
Senior, direct, no layers

Hire a Data Analyst for Game Studios: a data analyst turns scattered operational data into answers a manager can act on, with the caveats stated instead of hidden. Built around how game studios actually work, starting from the systems you already run.

15+
Years Experience
100+
Projects Delivered
6
Countries Served
$25M+
Revenue Enabled
Game Studios — Data Analyst

A senior data analyst for game studios

Live-ops content is planned in spreadsheets while the build pipeline, store deadlines, and certification windows all move on different calendars. A data analyst starts from that pattern, because it is where players feel the cost first.

A data analyst turns scattered operational data into answers a manager can act on, with the caveats stated instead of hidden. For game studios, that means work shaped around pre-production, vertical slice, alpha and beta, launch, and seasonal live-ops, with players, publishers, and platform holders as the people it ultimately serves. Because players, not viewers, are the audience, everything is tested against real play, not just review.

Games are interactive products, not linear content: players break things in ways no test plan predicts, and the work has to be built around that reality. The first step is a free discovery call on one real workflow, so the fit is proven before scope grows.

What you get

What this engagement covers for game studios

  • Build a dashboard that explains playtest feedback and build stability at a glance and caveats stated wherever the data is thin or messy.
  • Clean and join the data sources behind live-ops events and seasonal content and caveats stated wherever the data is thin or messy.
  • Build a regular report that replaces the manual spreadsheet for player telemetry and progression balance so the report updates itself instead of eating a morning a week.
  • Analyse store pages and launch checklists to find where time and money leak and caveats stated wherever the data is thin or messy.
  • Build forecasts for community reports and bug queues with uncertainty shown, not hidden with definitions agreed first, so the numbers are not argued about later.
  • Build definitions so everyone means the same thing by patch and hotfix releases with definitions agreed first, so the numbers are not argued about later.
The systems game studios actually run

Built on your stack, not on top of it

Most game studios already run on game engines, large-asset version control, automated build pipelines, live-ops tooling, playtest scheduling, store pages, and player telemetry. Information moves between those systems without one view of where a job stands. A data analyst connects that stack, using SQL, spreadsheets, BI tools, and reproducible analysis notebooks, and standardises the routines around it.

A change to a live game reaches every player at once, so releases are staged and rollback is planned before launch, not after. Analysis is only as good as its source data; where the data is unreliable, that gets said before any conclusion is drawn.

A sensible first project is one loop, such as playtest feedback into the next build, measured on how fast reported issues reach a fix or a decision. Nothing wider is agreed until that first job proves itself in daily use.

How it works

From kickoff to delivery for game studios

  1. Discovery and workflow pick

    One workflow first, usually playtest feedback and build stability, chosen from where game studios actually lose time, with a clear success measure agreed before build.

  2. Build on your existing stack

    The work starts from engines, build pipelines, and live-ops tooling and connects them, rather than replacing tools the team knows. A data analyst turns scattered operational data into answers a manager can act on, with the caveats stated instead of hidden.

  3. Review and harden

    Real game studios work is run through the result before launch: edge cases, errors, and the human review steps that must never be skipped, especially where age ratings and platform certification applies.

  4. Launch and improve

    Go live to one team or one workflow, measure against build stability, patch turnaround, and player retention across seasons, and expand scope only on evidence.

Why Omer

Why hire Omer

  • Dashboards that answer a question, not decorate a wall, measured for game studios by build stability, patch turnaround, and player retention across seasons.
  • Definitions agreed before numbers are debated, measured for game studios by build stability, patch turnaround, and player retention across seasons.
  • Caveats stated wherever data is thin, measured for game studios by build stability, patch turnaround, and player retention across seasons.
  • Reports that update themselves, measured for game studios by build stability, patch turnaround, and player retention across seasons.
  • Analysis the team can reproduce and check, measured for game studios by build stability, patch turnaround, and player retention across seasons.
Outcomes

What changes in practice

The realistic outcome is steadier builds, faster patch turnaround, and live-ops seasons that ship on the dates players were promised. Day to day, pre-production, vertical slice, alpha and beta, launch, and seasonal live-ops stop depending on heroic effort and start running on a routine the team can repeat.

That is the standard this engagement is measured against: not a launch announcement, but work game studios still use months later, maintained by their own team with documentation handed over at the end. Browse all hire engagements or discuss your workflow directly.

FAQ

Questions, answered

Will this work with engines, build pipelines, and live-ops tooling?
Yes. The work starts from the game studios stack you already run: game engines, large-asset version control, automated build pipelines, live-ops tooling, playtest scheduling, store pages, and player telemetry. A data analyst builds on those systems rather than replacing them, connecting SQL, spreadsheets, BI tools, and reproducible analysis notebooks where the work actually happens, so the team keeps tools it knows.
What about age ratings and platform certification?
Age-rating requirements, platform certification rules, consumer-protection rules for in-game purchases, and privacy rules for younger players all shape this work. Anything built here respects those duties from the start, and steps that carry regulatory consequences keep a human check. Analysis is only as good as its source data; where the data is unreliable, that gets said before any conclusion is drawn.
What is a sensible first project?
One loop, such as playtest feedback into the next build, measured on how fast reported issues reach a fix or a decision. One job done well gives the team something real to judge before wider scope is agreed, and the success measure is agreed before build starts.
Who inside game studios usually owns this work?
Usually the producer, with design and engineering leads on anything that changes gameplay or the build pipeline. The engagement is scoped so that owner can run it after handover, with documentation that does not depend on one person.
What if our data is messy?
Then cleaning comes first, and it is scoped honestly. For game studios, playtest feedback and build stability usually needs joining and definition work before any dashboard is trustworthy, and live-ops events and seasonal content is reported with its caveats until the source improves. A pretty chart on dirty data is worse than no chart.
Currently available for select engagements

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