What We Do

Kohort is the leading machine learning platform for mobile gaming user acquisition optimisation and financial planning. We provide game studios with investment-grade LTV predictions using petabyte-scale data and machine learning.

We are a group of gaming and data experts from King, Sensor Tower, Tripledot, Mistplay, Bloomberg and Football Radar. Our clients range from large, listed developers and publishers to up-and-coming start-ups building at the cutting edge of mobile gaming.

We add value to customers by helping them optimise UA spend on a day-to-day basis and then creating financial plans to accomplish strategic finance goals - from VC raises to IPO prep.

Our platform is investment grade; to date, we are the analytics partners of tier-1 VCs such as Index and CVC, and managed $8bn in deal value.

Why Work For Us

We consist of industry veterans and experienced tech company founders with successful venture exits. Our founding team consists of:

• Jan Pickard
• Dan Marcus

We've landed globally-known companies and been invested into by large US and UK VCs

Our Culture

Career acceleration:­ We are accelerating as only a­ startup can. Join us in a zero-politics, no-drama, high-energy, impact-focused environment on the ground floor.

Do the defining work of your career: We are working on a $6bn problem. That’s how much UA spend is wasted in mobile gaming each year. Did that make your blood boil? Sounds crazy? Wasteful? Let’s fix it together.

We live and breathe gaming: You’ll get to work with­ the biggest game studios and on the biggest gaming PE and VC deals. We also, of course, have frequent COD Mobile competitions.

Our Engineering Processes

ML engineers own the full lifecycle: from data exploration and model prototyping to deployment, monitoring, and iteration in production. We ship fast using a pragmatic, CI/CD-driven process with strong testing, observability, and model/version control. Teams operate in vertical squads with product, design, and data science, focused on delivering measurable impact. We balance velocity and rigor — building reusable ML systems, not one-off pipelines, and iterating quickly based on real user feedback.

Our Hiring Process

We perform an initial interview to gauge fit with Head of Engineering/Data Science, followed by 2 technical interviews, followed by a interview with the C-suite.

AI Focus

ML and AI are the core of what we do. We have a big drive to continually adjust to the new reality and adopting all the latest tools, thinking and building our own Agents