Machine Learning Engineer – MTS

Company Description

We're the world's leading sports technology company, at the intersection between sports, media, and betting. More than 1,700 sports federations, media outlets, betting operators, and consumer platforms across 120 countries rely on our know-how and technology to boost their business.



Job Description

ABOUT US:

As a Machine Learning Engineer in Sportradar'sAI unit, you will work within an established, high performing team of experts on the design, development and deployment of predictive models and algorithms powering Spotradar'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.

 

THE CHALLENGE:

• Analyse 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.
• Rigorously validate methods, models, algorithms and hypotheses using back-testing on historical data and/or simulations.
• Bring models into production leveraging our AI platform, maintaining ownership of the AI solution throughout the model development lifecycle, from modelling to production deployment, monitoring and continuous model improvement.
• 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.
• Present ideas and solutions to software developers and business stakeholders in a clear and understandable way

 

ABOUT YOU:

• At least 3 years of professional experience on a similar field or position (Data science, Machine Learning etc.).
• Good knowledge of machine learning and statistics.
• Strong programming skills and software development experience needed to productize low latency streaming analytics solutions are a must (Java/C#/C++ and Python).
• 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.
• Bonus: Hands-on experience with real-time streaming analytics frameworks such as Apache Flink and streaming technologies such as ApacheKafka.
• 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.

 

OUR OFFER:

• A collaborative environment with colleagues from all over the world (Engineering offices in Europe, Asia and US).
• Ability to shape your own workday and career via a clearly defined professional and personal development plan.
• Opportunity to work with seniorleadership team and developyourself within an inspiring and fast-growing company.
• Vibrant and inclusivecommunity, including Women in Tech and Pride groups which welcome all participants.
• Hybrid work model.
• New office with several additional benefits.

 



Additional Information

At Sportradar, we celebrate our diverse group of hardworking employees. Sportradar is committed to ensuring equal access to its programs, facilities, and employment opportunities. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. We encourage you to apply even if you only meet most of the requirements (but not 100% of the listed criteria) – we believe skills evolve over time. If you're willing to learn and grow with us, we invite you to join our team!