Gaming Data Scientist- Blitz

Location🇫🇷Paris

PostedJul 23

Stack: Python

About Voodoo

Voodoo is a consumer tech company founded in Paris in 2013, with one mission: entertain the world. Today we are 1,000 people, generating $1b+ in annual revenue, profitably. Our games and apps have passed 7 billion downloads and reach 200 million+ active users every month, making Voodoo the #3 mobile publisher worldwide in downloads, after Google and Meta. We were backed by Goldman Sachs, Tencent and GBL along the way.

Team

Blitz is a gaming platform launched by Voodoo in 2021, allowing players to compete on mobile games for real cash prizes (head-up, tournaments, leagues, etc.). It is leveraging Voodoo's unique game portfolio to engage users in a fun and rewarding way.

Role

This role sits at the intersection of the Data and Gaming teams. You'll be the analytical partner to game designers and product managers, owning the measurement and tuning of the games themselves — from difficulty and game parameters to matchmaking fairness and the in-game economy. Your work directly shapes what players experience and how the games perform.

Missions:

Own the A/B testing cycle for games and game parameters — designing experiments, validating changes, and reading out results that drive core KPIs (engagement, RTP, rake, fairness, retention).
Analyze and calibrate game parameters — difficulty, scoring, completion rates, seed selection, and payout structures — to hit target player experience and economic goals.
Translate analyses into clear, actionable recommendations that shape game design and the product roadmap.
Build simulations and prototypes to pressure-test parameter and economy changes before rollout, then monitor them live once shipped.
Collaborate closely with game designers and engineers to embed data-driven decisions across the full game lifecycle.
Build and maintain dashboards and reports that keep the Gaming and Data teams aligned on critical game and economy metrics.

Profile

3+ years in analytical roles, ideally within gaming or a data-intensive product environment, comfortable working directly with product and design teams.
Skilled in SQL and Python; experience with large, complex datasets.
Strong grasp of A/B testing and statistical methods.
Comfortable with simulation and modeling to reason about game parameters, difficulty, and game economy outcomes.
Thrives in a fast-paced environment with rapid iteration.
Player-first mindset with genuine curiosity about games, player behavior, and game balance.