As the Senior Director of Data Science, you will be a transformational leader, responsible for guiding and inspiring a talented team of data scientists and machine learning engineers. In this role, you’ll drive the thought leadership and development of cutting-edge data solutions that enhance gameplay, improve user engagement, and optimize business outcomes. You will be a key partner for cross-functional teams—including product management, game operations, and growth—leveraging your data expertise to deliver engaging mobile games as well as industry-leading marketing performance.

WHAT WE NEED FROM YOU

PhD or MSc in Data Science, Computer Science, Statistics, Physics, or a related field.
Experience: 10+ years of data science experience, with a minimum of 5 years in a leadership role, managing teams in dynamic and collaborative environments.

TECHNICAL SKILLS:

• Proven expertise in clustering, predictive modelling, reinforcement learning, and Bayesian statistics.
• Experience in reinforcement learning and Agentic systems would be ideal
• Experience in ML Ops and deploying machine learning models at scale.
• Proficiency in Python or R, and familiarity with big data technologies (e.g., Hadoop, Kafka) and/or cloud platforms (e.g., GCP or Azure).
• Industry Knowledge: Experience in gaming or digital entertainment is a strong plus.
• Communication & Influence: Exceptional communication and interpersonal skills, with the ability to inspire and influence stakeholders at all levels of the organization, from junior analysts to executive leadership.

KEY LEADERSHIP RESPONSIBILITIES

• Visionary Leadership: Define and communicate a clear vision and strategy for data science, ensuring alignment with organisational goals while inspiring your team to innovate and excel.
• Mentorship & Development: Provide ongoing mentorship, coaching, and professional development opportunities to foster growth and enhance team performance. Create a collaborative and high-performance team culture that attracts top talent and encourages long-term career progression.
• Stakeholder Partnership: Act as a trusted advisor and thought leader across the organisation, particularly with senior executives and cross-functional leaders, advocating for data-driven decision-making and empowering business units to leverage data science insights.
• Change Management: Lead the adoption of data science practices and continuous improvement, managing agility, ROI, and keeping the company up to date with evolving industry trends.
• Ownership & Accountability: Assume full accountability for the data science function, from project execution to final integration and outcome assessment, ensuring that your team delivers impactful results on time and within scope.

KEY TECHNICAL RESPONSIBILITIES

• Data Science Strategy & Best Practices: Drive best practices in A/B-testing, predictive modelling, user clustering and reinforcement learning, to continually raise the bar on data science value add.
• Infrastructure Ownership: Lead the development of data science frameworks, including A/B testing and other data science tooling. Ensuring scalability, accuracy, and reliability across projects.
• Product & Engineering Collaboration: Oversee integration of data science solutions into games and platforms, partnering closely with product and engineering to ensure end-to-end solution success.
• Growth & Marketing Innovation: Collaborate with growth and marketing teams to develop advanced prediction models that support a dynamic, high-performance marketing landscape.
• Insight Communication: Translate complex analytical insights into actionable recommendations, presenting them to the senior leadership team to inform critical business decisions.