Job Description
Job Description
Why This Role Exists
Games generate mountains of data — player behavior, progression curves, economies, feature experiments, live ops events. The challenge isn't collecting it. It's turning it into decisions that make games more fun, more engaging, and more profitable.
We're looking for a gaming-savvy data scientist who can uncover player insights, balance competing KPIs, and help shape game design using evidence — not guesswork. If you enjoy digging into player funnels, A/B test results, and economy models to answer “why did players do that?” — you'll fit right in.
What You'll Do (Your Day-to-Day in Game Terms)
- Analyze player behavior, engagement, retention, monetization, and progression across our games
- Design and maintain dashboards that track live game performance and guide real-time decisions
- Partner closely with Game Designers, Product, Live Ops, and Game Intelligence teams to embed data into design and operational choices
- Define and evolve core game KPIs (DAU/MAU, ARPDAU, LTV, churn, conversion, feature performance)
- Lead A/B tests and experiments to evaluate features, balancing changes, and live ops events
- Translate complex player data into clear insights and narratives that non-data teammates can act on
- Help drive a culture where data informs game design — without killing creativity
- Stay current on game analytics trends, tools, and best practices
Nice-to-Haves (a.k.a. “You'll impress us if you bring these”):
- Building predictive models for churn, LTV, player segmentation, or personalization
- Advanced statistical modeling or simulation for game economies and feature impact
What You Bring to the Table
- Bachelor's degree in Statistics, Applied Mathematics, Computer Science, or a related field
- Hands-on experience with A/B testing, experimentation, and feature analysis
- Strong problem-solving skills and comfort working in ambiguous, real-world game scenarios
- 4+ years of industry experience in data science, analytics, ML, or predictive modeling (preferred)
- Experience applying machine learning or AI where it actually adds value (not just because it's cool)
- Master's degree preferred for senior-level candidates
- Highly preferred: experience working with online gaming datasets, especially slot or casino-style games
Your Analytics Toolkit
- Data & BI tools: SQL, Snowflake, Tableau, Power BI, Excel
- Programming & analysis: Python, R, Java, SAS
- Machine learning & AI platforms: TensorFlow, Azure ML Studio, or similar
- Strong foundation in statistics, data mining, pattern recognition, and predictive modeling
Why Gaming Data Scientists Like This Role
- Your insights directly influence game design, player experience, and revenue outcomes
- You'll work alongside designers and product leaders who actually want data at the table
- You'll analyze live games with real player impact, not abstract datasets
- You'll help balance the art and science of game development
If you love games, think in funnels and cohorts, and enjoy turning player data into smarter design decisions — we'd love to hear from you.