Data Science Manager

Role overview A leadership role managing a data science team that serves product, marketing, and performance functions within a social casino and gaming organization. The position combines hands-on technical review with people management, ensuring rigorous experimentation, modelling quality, and clear translation of business needs into team priorities.

Responsibilities - Partner with senior leadership to shape and prioritize the data science roadmap so work stays aligned with business goals - Translate stakeholder needs into clear team priorities, manage expectations proactively, and communicate trade-offs and results in accessible terms - Review modelling approaches, experimental design, and causal inference work, stepping in directly to pair, deliver, or course-correct when needed - Hire, coach, and grow data scientists, run regular 1:1s, and partner on performance, compensation, and career development - Champion sound A/B testing, quasi-experimental methods, and causal thinking across both product and performance tracks

Requirements - Hands-on data science background with a track record of delivering models, experiments, or analyses that other teams actually used - Demonstrated depth in at least one domain such as Recommendation Systems, Experimental Design and Causal Inference, Customer Segmentation, Churn Prediction, Fraud or Anomaly Detection, or CRM analytics, with product-focused experience especially valued - Strong command of statistical methods, supervised and unsupervised machine learning, and causal inference - Experience leading others as a tech lead, mentor, or hiring interviewer; prior formal people-management experience is a plus - Proficiency in Python and SQL - Ability to give precise technical feedback to data scientists while representing the team clearly to senior non-technical stakeholders

Nice to have - Familiarity with cloud-based data and ML platforms such as AWS, GCP, or Azure