Gangstar Vegas

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Timeline: 2013 to 2015

Platform: Mobile (iOS and Android)

The Game: Gangstar: Vegas is the fifth main game in the Gangstar open world action and driving series and this time it is set in the city of Las Vegas. The protagonist is Jason Malone, an MMA fighter. He is pressured by the mafia boss Frank Veliano to throw a fight, but knocks out his opponent too soon and has to flee. He is saved by Karon Olsen, the accountant and bodyguard of Vera Montello, the wife of the rival and late mafia boss Johnny Montello. This is the start of a series of story missions where Jason works for Vera and needs to escape Veliano and the police who are bribed by the mafia boss.

My Contributions

The Gangstar franchise can be thought as "GTA for mobile". Vegas was launched as premium game, and the initial stat of its economy was thought exclusively to be a one-time campaign play, much like an "old school" console title.

When I joined the team a few months after launch, my mission was to prepare this title to go free-to-play, which required major changes to its economic systems. With Gameloft's Ukraine studio, I game designed changes and new features to turn around business for this game. The shift was a major boost to its sustainability as a Live Ops product, and the title was still profitable 10 years later.

Design & UXProduct & DataEngineering
  • Worked with the development team to tune and prepare the game to transition between the Premium model to free-to-play;
  • Revamped all the economy balancing methods and spreadsheets in order to have a mode consistent way to price and assign Lottery chances on new items during Live Ops.
  • Game economy re-design, successfully moving a premium-first, pay-to-download game into a free-to-play model;
  • Game economy balancing: the reward curve and a new loot crate system required major re-haul of the balancing spreadsheets;
  • Designed new Bundle Pack and VIP systems that  improved the IAP revenue per DAU by up to 38%, and the IAP revenue per paying user by up to 48%;
  • Data analysis: as I needed data about specific interactions of our players, cohorted by progression milestones such as XP level, I leaned in my past experience with programming and databases to query and extract insights from our BI database. Used Python with Pandas, Statsmodel and Sublime Text.
  • Modeled an economic simulation in Excel, which projected the resource utilization and progression of a typical player across a full year of sessions.


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