Senior Data Scientist - CLV & Personalisation

As a Senior Data Scientist, you will drive the development of advanced modeling and analytical approaches that influence key commercial and product decisions at scale. You will work on complex and often ambiguous problems, helping define how we measure player value and how we deliver more personalized player experiences. This role combines deep hands‑on modeling with ownership of problem definition, approach, and impact. You will work with a high degree of autonomy across ambiguous problem spaces, shaping how data informs strategy and decision‑making across the business.

What You’ll Do

• Design and deliver advanced machine learning models to drive player value, engagement, and growth across the lifecycle.
• Own ambiguous problem spaces, defining modeling approaches and breaking down complex business challenges into actionable solutions.
• Partner with senior stakeholders to shape strategies, and ensure Data Science drives high‑impact decisions.
• Apply advanced machine learning techniques, including deep learning and sequence modeling, where appropriate to capture complex player behaviors and improve model performance.
• Evaluate and select modeling approaches based on problem context, balancing performance, scalability, and interpretability.
• Work within cross‑functional teams, including engineering, product, and commercial stakeholders, to ensure solutions are scalable, production‑ready, and aligned with long‑term architecture.
• Mentor other data scientists and contribute to best practices across the team.
• Communicate complex modeling approaches, assumptions, and outcomes clearly to senior technical and non‑technical audiences.

Qualifications

• Proven industry experience delivering impactful, production‑ready machine learning solutions in areas such as customer value, retention, or personalization.
• Strong expertise in modern machine learning approaches, including applying techniques such as transformers, embeddings, or sequence‑based models to real‑world behavioral data.
• Ability to critically assess when advanced approaches are warranted versus simpler solutions.
• Experience owning projects end‑to‑end, including problem definition, navigating ambiguity, selecting modeling approaches, and delivering impactful solutions.
• Ability to work with large, complex datasets and translate them into scalable solutions.
• Strong stakeholder management and communication skills, with the ability to influence decisions and communicate results persuasively to both technical and non‑technical audiences.
• Proficiency in Python, SQL, and modern ML tooling (such as TensorFlow, PyTorch, MLlib, feature stores); experience with PySpark or equivalent distributed data processing tools.
• A strong academic background, typically a Master’s or PhD in a technical or quantitative field, specializing in Machine Learning.
• Experience deploying models into production and maintaining business‑critical or consumer‑facing models.
• Experience working in agile, fast‑paced environments.

Nice to Have

• Background in gaming, e‑commerce, or subscription‑based businesses.
• Industry experience with experimentation frameworks and causal inference.