Lead Data Scientist in London

About Kohort

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. 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 PEs and VCs such as Index and CVC, and managed $8bn in deal value.

Why Kohort

• 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.
• Shape the DS function from day one: As our Lead Data Scientist, you will define the technical direction, culture, and working practices of the data science team.
• We live and breathe gaming: You'll get to work with the biggest game studios and on the biggest gaming PE and VC deals.

Your Role

As Lead Data Scientist at Kohort, you’ll own the technical direction and delivery of our machine learning capabilities, driving the innovations that power our investment-grade analytics platform. You’ll work alongside software developers, product managers, and data scientists to build and refine the ML models and data systems that deliver actionable insights to our clients. You will be the most senior data science practitioner in the company and will report directly to the founding team.

Technical Vision & Strategy: Define and own the data science roadmap. Evaluate new techniques, frameworks, and data sources to keep Kohort at the frontier of gaming ML. Make build-vs-buy decisions and set technical standards for the team.

Model Innovation: Design and implement sophisticated ML models for LTV prediction, user acquisition optimisation, and financial forecasting, focusing on understanding complex gaming behaviours and developing out-of-the-box solutions.

Team Leadership & Development: Mentor and grow a small but high-performing data science team. Lead hiring as the team scales. Establish code review practices, model validation standards, and a culture of rigorous experimentation.

Stakeholder Communication: Translate complex model outputs into clear, actionable narratives for clients, investors, and C-level executives. Represent Kohort’s data science capability externally.

Data Detective: Proactively identify and integrate new data sources, thinking creatively to solve complex data challenges. Constantly look for unconventional data that could unlock new insights.

Performance & Scale: Optimise model performance and scalability to handle petabyte-scale gaming data while maintaining investment-grade accuracy standards.

Domain Expertise: Continuously deepen your understanding of gaming analytics, user acquisition mechanics, and mobile gaming business models to inform better modelling approaches.

We are a Series A startup. So we know our domain and the problems we solve, but we want your help in pioneering the solutions. Part of this role is being a startup operator, executing cutting-edge research while helping build the company simultaneously.

Requirements

• Location: Europe to for solid cross over with GMT+2 timezones and rest of teams. If London based, 2 days in office.
• Experience: 5+ years of experience in hands-on data science and machine learning at scale. Experience in gaming or AdTech is required.
• Education: Master's degree or higher in Data Science, Statistics, Mathematics, Computer Science, Physics, or related quantitative field. PhD preferred.

Technical Proficiency

• Expertise in Python, with advanced proficiency in SQL for complex data manipulation.
• Deep experience with machine learning frameworks (scikit-learn, PyTorch, XGBoost) and statistical modelling techniques.
• Strong background in time series forecasting and predictive modelling for business applications.
• Proven track record in MLOps practices, model deployment, and production ML infrastructure (e.g. orchestration tools like Dagster or Airflow, containerised deployments on AWS/GCP/Azure).
• Experience with LLMs, AI coding assistants, and a strong desire to leverage cutting-edge AI techniques effectively.
• Ability to make pragmatic architectural decisions around data pipelines, model serving, and experimentation infrastructure.

Mindset & Leadership

• Extremely proactive, self-driven attitude with exceptional creative problem-solving abilities in a fast-paced startup environment.
• Demonstrated ability to set technical direction and make high-judgement calls on scope, prioritisation, and trade-offs.
• Experience hiring, mentoring, and developing data scientists – building a team culture of rigour, velocity, and intellectual curiosity.
• Insatiable curiosity for discovering new data sources and unconventional approaches to complex analytical challenges.
• Pragmatic, business-outcome-oriented approach with ability to translate sophisticated models into clear business value.
• Outstanding communication skills with ability to present complex findings to technical teams, clients and C-level executives.
• Collaborative mindset with experience working across cross-functional teams in high-stakes environments.

What you’ll receive

• Competitive salary.
• Employee Share Scheme.
• Income protection and Life cover.
• Wellbeing rewards.
• Employee Assistance Program.