Senior Data Scientist

About the 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, 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.

• 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.

• 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, Num Py, XGBoost.
• Advanced proficiency in SQL, with hands-on experience querying and manipulating large, complex datasets, preferably with Google Big Query.
• 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 Big Query, 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 Git Lab CI for automating ML workflows.
• Experience with containerization such as Docker, Kubernetes/GKE.