Senior Data Scientist

hackajob is collaborating with Bet365 to connect them with exceptional professionals for this role. As a Senior Data Scientist, you will accelerate our end-to-end machine learning lifecycle, building on our strong data science foundation to scale impact and automate business decisions. The data science team is at the forefront of driving business decisions; we are now scaling our impact with a focus on automation and advanced MLOps practices on Google Cloud. This is a key technical leadership role where you will champion rapid iteration and innovation, this will be instrumental in elevating our ability to deliver measurable value. You will be responsible for the end-to-end lifecycle of machine learning solutions that optimize our Sports and Gaming products, from development to automated deployment and monitoring. This is an exciting opportunity to apply cutting-edge data science and MLOps principles in a fast-paced, high-impact environment, tackling complex challenges in areas like Trading, Fraud, Responsible Gaming, and Personalization. Main Responsibilities: In this hands-on role you will devise, code, and deploy AI, machine learning and predictive models, leading by example in technical execution and code quality. This is not a pure people-management role. Building, mentoring, and guiding a pragmatic, delivery-focused team of Junior Data Scientists and Machine Learning Engineers, fostering a culture of rapid iteration, continuous learning, and software engineering discipline. Partnering closely with the Data Team Lead, Data Product Lead, and AgentOps Team Lead to align data science initiatives with product roadmaps and platform capabilities. Collaborating regularly with our UK-based Data Science team of technical excellence to share methodology, align on standards, and leverage global technical capabilities. Translating complex, ambiguous business questions into clear data science initiatives, delivering measurable business value through rapid prototyping and deployment cycles. Collaborating with Machine Learning Engineers to champion the adoption of robust MLOps practices on our Google Cloud Platform (GCP) stack, ensuring models are automated, monitored, and scalable. Establishing data science workflows, standards, and code repositories from scratch in a new regional office. The skills and experience to help you perform in the role: Proven experience working in a fast-paced, agile, or startup-like environment. You must have a demonstrated passion for “getting things done” and delivering value iteratively. Prior experience mentoring, coaching, or leading data scientists or engineers while remaining active in code development. A strong track record of designing, building, deploying, and maintaining machine learning models in production environments Superior communication skills with the ability to build strong cross-functional relationships and translate technical concepts into business outcomes for both technical and non technical audiences. Exceptional programming skills in Python and deep expertise in data science libraries (Scikit-learn, Pandas, NumPy, XGBoost, etc.). Advanced SQL proficiency for querying and manipulating large datasets, preferably within Google BigQuery. Hands-on experience with Google Cloud Platform (GCP), ideally including the Vertex AI ecosystem (Pipelines, Workbench, Endpoints). MSc or PhD in a quantitative discipline (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical industry experience. Familiarity with containerization (Docker, Kubernetes) and CI/CD principles for machine Experience with real-time stream processing or event-driven architectures (e.g., Kafka).aa415a4b-8b21-40fc-a65c-70d2b25ca29a