Senior Data Scientist - MTS

As a Data Scientist in Sportradar's AI unit, you will work within an established, high performing team of experts on the design, development and deployment of predictive models and algorithms powering Sportradar’s products. You will leverage Sportradar's extensive sports datasets, betting transaction data and user interaction data collected through Sportradar's products and services reaching millions of end-users across the globe. The position will be focused on the development of AI and advanced analytics solutions for sportsbook risk management and liquidity driven odds trading, collaborating closely with product owners and technical leads in our Managed Trading Services and Odds Services product domains. You will analyze and explore data using statistical analysis tools and scripting, develop machine learning or statistical models for use in our sportsbook risk management and odds trading products and services, and rigorously validate methods, models, algorithms and hypotheses using back-testing on historical data and/or simulations. You will bring models into production leveraging our AI platform, maintaining ownership of the AI solution throughout the model development lifecycle, from modeling to production deployment, monitoring and continuous model improvement. Additionally, you will design and implement novel methods for data analysis, tailored to our sports-related application domains and propose new ways of using data to improve our products and services. Presenting ideas and solutions to software developers and business stakeholders in a clear and understandable way is also a key part of the role.

Knowledgeable in machine learning and statistics, strong programming skills and software development experience, experience with risk management and portfolio optimization in financial, gaming or sports betting contexts is a plus, experience in data science, statistical modelling, applied mathematics and/or software engineering, proficiency with advanced querying of large analytical databases using SQL, programming experience, experience with Python, R or similar statistical and/or machine learning software/toolkits, bonus: experience working in Java, bonus: hands-on experience with real-time streaming analytics frameworks such as Apache Flink and streaming technologies such as Apache Kafka, bonus: experience working with Mac/Linux environments, Bachelor of Science in Mathematics / Statistics, Computer Science / Engineering, or related field; equivalent experience acceptable, fluent in English (written and spoken), autonomous, rigorous, creative and a team player.