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Sportradar is seeking a Senior Data Scientist to join its AI unit, working within an established, high-performing team focused on designing, developing, and deploying predictive models and algorithms that power Sportradar's products. You will leverage Sportradar's extensive sports datasets, betting transaction data, and user interaction data collected through products and services reaching millions of end-users globally.
The position focuses on developing AI and advanced analytics solutions for sportsbook risk management and liquidity-driven odds trading, collaborating closely with product owners and technical leads in the Managed Trading Services and Odds Services product domains.
Key Responsibilities:
- Analyze and explore data using statistical analysis tools and scripting
- Develop machine learning and statistical models for sportsbook risk management and odds trading products
- Rigorously validate methods, models, algorithms, and hypotheses using back-testing on historical data and simulations
- Bring models into production leveraging the AI platform, maintaining ownership throughout the model development lifecycle from modeling to production deployment, monitoring, and continuous improvement
- Design and implement novel methods for data analysis tailored to sports-related application domains
- Propose new ways of using data to improve products and services
- Present ideas and solutions to software developers and business stakeholders clearly
The company operates on a fully on-site model with team members working in the office five days a week, though certain exemptions may apply depending on location. The role offers a collaborative environment with colleagues worldwide, flexible working hours, global employee assistance programs, and access to well-being apps and online training.
Requirements:
- Strong knowledge in machine learning and statistics
- Strong programming skills and software development experience required to productize low-latency streaming analytics solutions
- Proficiency with advanced SQL querying of large analytical databases
- Experience with Python, R, or similar statistical/machine learning software toolkits
- 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
Preferred Qualifications:
- Experience with risk management and portfolio optimization in financial, gaming, or sports betting contexts
- Background in data science, statistical modeling, applied mathematics, or software engineering
- Experience with Java
- Hands-on experience with real-time streaming analytics frameworks such as Apache Flink and streaming technologies such as Apache Kafka
- Experience working with Mac/Linux environments
