Senior Data Scientist

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.

The listed salary for this position is $135,000 – $150,000 annually.

Qualifications

• PhD or MSc in a quantitative field such as Computer Science, Statistics, or Engineering, or equivalent industry experience delivering complex data science projects.
• Demonstrable experience deploying and maintaining machine learning systems in a production environment with measurable business impact.
• Strong programming skills in Python and deep expertise in data science libraries such as, Scikit-learn, Pandas, NumPy, XGBoost.
• Advanced proficiency in SQL, with hands-on experience querying and manipulating large, complex datasets, preferably with Google BigQuery.
• Extensive hands-on experience with Google Cloud Platform (GCP), including building and automating ML workflows with Vertex AI pipelines, managing datasets, training models, and deploying to Vertex AI.
• Experience using collaborative development environments such as Vertex AI Workbench for rapid prototyping, exploration, and analysis.
• Experience leveraging other core GCP services such as BigQuery, Cloud Storage, and Cloud Functions to build end-to-end data solutions.
• Solid understanding of CI/CD principles and tools such as Cloud Build or GitLab CIfor automating ML workflows.
• Experience with containerization such as Docker, Kubernetes/GKE.

Additional Information

• Owning the full data science lifecycle, from initial ideation and rapid prototyping in tools such as Vertex AI Workbench, to deploying production-grade models and pipelines that are robust, scalable, and automated.
• Leading the implementation of advanced MLOps principles within our Google Cloud environment, designing, building, and maintaining CI/CD/CT pipelines for automated model deployment using Vertex AI Pipelines and other GCP services.
• Partnering proactively with stakeholders in Product, Responsible Gaming, Trading, and other teams to identify high impact opportunities and translate complex business needs into tangible data science use cases.
• Building and implementing frameworks for automated model testing, validation, and monitoring using tools such as Vertex AI Model Monitoring to detect drift and ensure performance at scale.
• Designing, implementing, and rigorously analyzing A/B tests and other experiments to measure the impact of models and strategies, ensuring data-driven solutions deliver clear, quantifiable value.
• Researching and championing the adoption of innovative data science and MLOps techniques, tools, and methodologies that solve problems efficiently, prioritizing impact over complexity.
• Acting as a technical leader and mentor for other data scientists, fostering a culture of continuous learning and high-velocity execution.

bet365 provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.