Data Science Lead

Lead Data Scientist- Trading Efficiency Team

Job Description

As a Lead Data Science Engineer for our Trading Efficiency team, you will be part of a new team that will build a platform that will help optimize efficiency and build automation within our Sportsbook. You’ll build complex low latency systems to support data science decision-making at scale, to unlock more value for the business. This team is part of our Sports Intelligence group which plays a critical role in developing solutions that power our platforms and drive our business forward.

 What You'll Do as a Lead Data Science Engineer

·       Lead and mentor a team of data scientists and engineers to achieve high-impact business goals.

·       Develop and implement advanced machine learning models and algorithms to solve complex business problems.

·       Collaborate with cross-functional teams to integrate data science solutions into production systems.

·       Drive the adoption of data-driven strategies into the trading processes​​​​

·       Drive the design, development, maintenance, and testing strategy of trading automation solutions, ensuring alignment with overall business objectives

·       Communicate findings and recommendations to senior leadership to influence strategic decision-making.

What You'll Bring

·       Extensive experience in data science, machine learning, and statistical modeling, with a proven track record of leading successful projects.

·       Proficiency in programming languages such as Python or R, and experience with data manipulation and visualization tools.

·       Strong leadership skills with the ability to mentor and develop a high-performing team.

·       Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

·       A Master's or PhD in a relevant field such as Computer Science, Statistics, or Mathematics is preferred.

·       Experience with typical DevOps flows, such as containerisation and monitoring

·       Experience in developing and implementing automated trading or decision-making systems is highly desirable​​​​

·       Experience with Kubernetes and Kafka are desirable

·       Experience with Databricks is desirable