VP of AI

Job Description

The role is leading the Group data&ML team

The team is a central function that works both with other central group functions like marketing and game solutions, and the game studios which are part of  Tripledot. Within the team, you’ll be working with other AI/ ML Eng, Data engineers, ML Ops, Data scientists, analysts and product owners. 

Role Overview

We are looking for a practical, commercially-minded, results-oriented person to collaborate with studios and group functions and lead AI/ML/Data initiatives that will leverage our group’s scale, help bring new capabilities that will enhance our games, monetisation, and user acquisition.  You’ll lead a team of ML engineers and data scientists to turn AI/ML into measurable business outcomes — increasing player lifetime value, improving monetization efficiency, driving higher ROI on ad spend, and accelerating content scalability.

This is a strategic leadership role where you’ll shape technology and teams, own impact at the business level, create collaborations, and help shape games’ development vision,with the goal of supporting growth and competitive edge.

Key Responsibilities

• Identify initiatives with a direct focus on revenue generation and business KPIs.
• Prioritize initiatives that directly improve LTV, retention, ARPU, ROAS, and operational efficiency.
• Deliver robust, production-ready ML systems across multiple verticals.
• Leverage AWS SageMaker, Snowflake, and internal tools with strong MLOps practices.
• Build and manage a high-performing AI/ML team of 10–20 professionals.
• Promote a culture of ownership, delivery excellence, and continuous team growth.
• Integrate ML and data initiatives into game and marketing operations.
• Work with C-level, Product directors, and technical directors across game teams.

Required Skills, Knowledge and Expertise

• 10+ years of experience in AI/ML/Data Science, with 6+ years in senior leadership roles.
• Proven track record of delivering AI/ML impact on business KPIs such as LTV, ROAS, ARPU and retention.
• Executive presence with strong stakeholder communication skills across technical and non-technical audiences.
• Hands-on experience with user-level and performance marketing data.• Proficiency with AWS (SageMaker, Lambda, Step Functions), Snowflake, and modern MLOps tooling.
• Familiarity with ML frameworks including PyTorch, TensorFlow, scikit-learn, and XGBoost.
• Experience managing and scaling high-performing data science and ML engineering teams.