Lead Data Scientist

A fast-moving team working at the forefront of mobile advertising is looking for a Lead Data Scientist to help shape the future of programmatic monetisation. This role offers the opportunity to work on real-time bidding systems where ads are auctioned and rendered in milliseconds across thousands of mobile apps. The team develops advanced algorithms and data-driven systems that directly compete with some of the biggest names in the industry. With a focus on research-driven innovation, the team aims to balance the needs of users, publishers, and advertisers while maintaining a high-quality user experience. The Lead Data Scientist will be responsible for growing and mentoring a team, driving technical direction, and contributing directly to data science projects. At least half of the role will involve hands-on work, with the remainder focused on leadership, collaboration, and strategic planning. Key Responsibilities

• Build and lead a high-performing data science team, including hiring, mentoring, and setting best practices
• Translate business goals into data solutions that strengthen the competitiveness of the ad platform
• Work on data science tasks individually, contributing significantly to project outcomes
• Document experiments, methodologies, and implementation details clearly
• Collaborate closely with product, infrastructure, and business teams
• Contribute to strategic planning and define quarterly and long-term objectives

Required Skills and Experience

• A degree in mathematics, physics, computer science or equivalent experience in data science (minimum 5 years)
• At least 2 years of leadership experience, including line management and career development support
• Strong programming skills in Python, R, Scala, Julia or similar languages
• Proven analytical skills and a solution-oriented mindset
• Experience working with large-scale data platforms such as AWS Athena, Kafka, Spark, Flink, and S3
• Expertise in scaling recommendation systems
• Ability to explain complex mathematical concepts in simple terms
• Excellent communication skills and experience working across teams

Desirable

• Experience building and selecting technologies for a modern data science tech stack (e.g. Airflow, Kafka, Flink)
• Understanding of MLOps and collaboration with engineering teams

Benefits and Perks

• Hybrid working model with up to two remote days per week and three weeks per year of remote work from anywhere
• 30 days annual leave
• Comprehensive relocation support including visa assistance, relocation bonus, and reimbursement for language courses
• Monthly company lunches, snacks, and fresh pastries
• Access to an in-house gym, personal trainer, and wellness classes
• Frequent team and company events
• Budget for professional development, training, and certifications
• Equity programme for full-time employees
• Mental health and wellbeing support through a dedicated assistance programme