Data Scientist (m/f/d)

ABOUT US: 

As a Data Scientist at Sportradar, you will work with world leading experts to design and develop data-driven predictive models and algorithms aimed at improving Sportradar's products and services. You will explore large collections of sports and betting data, focusing on the development of AI models, or sophisticated alerting systems to detect fraudulent activity in the sports betting industry, or for commercial awareness. You will work closely with product owners and technical leads in our integrity services product vertical.

The successful candidate will be knowledgeable in machine learning and statistics, be comfortable working with big datasets, understand methods for rigorous validation of results, and have experience working with GenAI tools and scripting to develop LLMs and assist with modelling.

THE CHALLENGE:

• Rigorously validate methods, models, algorithms and hypotheses using back-testing on historical data and/or simulations.
• Design and implement a supervised model and LLMs on our existing solutions. 
• Propose new ways of using data to improve our products and services.
• Able to combine data from different sources (external and internal) and formats to create meaningful insights or alerts. 
• Work closely with product owners and technical leads, and analysts to implement or improve new or existing solutions/features.
• Present ideas and solutions to software developers and business stakeholders in a clear and understandable way. 

ABOUT YOU: 

Must have:

• Proven experience in data science, data engineering, or software development, ideally with exposure to AI-driven applications.
• Hands-on experience with Git.
• Strong proficiency in Python (including libraries for data manipulation, visualisation, and ML).
• Experience with advanced querying of large analytical databases using SQL.
• Hands-on experience with developing reporting solutions and interactive dashboards using BI tools such as PowerBI.
• Bachelor of Science in Mathematics / Statistics, Computer Science / Engineering, or related field; equivalent experience acceptable.
• Fluent in English (written and spoken).
• Ability to work autonomously, with rigour, creativity, and strong team collaboration skills.

Nice to have:

• 2+ years of experience in data science, data analytics, data engineering, or software engineering.
• Familiarity with Large Language Models (LLMs) and their integration into applications.
• Experience with MLOps, DevOps, or Data Engineering workflows.
• Hands-on experience with cloud platforms (AWS services such as S3, Redshift, Athena, EMR).
• Knowledge of API development/integration.
• Expertise in anomaly detection and a strong analytical mindset for fraud prevention.
• Experience working in macOS environments.
• Interest in sports.

OUR OFFER:

• A collaborative environment with colleagues from all over the world (Engineering offices in Europe, Asia and US) including various social events and teambuilding. 
• Flexibility to manage your workday and tasks with autonomy. 
• A balance of structure and autonomy to tackle your daily tasks. 
• Vibrant and inclusive community, including Women in Tech and Pride groups which welcome all participants. 
• Global Employee Assistance Programme. 
• Calm and Reulay app (leading well-being apps designed to support focus, quality rest, mindfulness, and long-term mental resilience). 
• Online training videos. 
• Flexible working hours. 

While we appreciate the flexibility and benefits of working from home, we strongly believe that coming together in person fosters stronger connections, encourages collaboration, and drives innovation—both as individuals and as a company. The energy, shared ideas, and team support we experience in the office strengthen the foundation of our success and culture. For this reason, we are an office-first business operating on a hybrid model, with team members working in the office three days a week to build relationships, exchange ideas, and grow together. 

OUR RECRUITMENT PROCESS: 

• Initial Screening: A quick chat with our Talent Acquisition Partner to understand your background and expectations. 
• Technical Assessment: A short task to showcase your technical skills. 
• Technical Interview: Meet with the Technical team and Hiring Manager to dive into your solution, as also discuss team fit. 
• Onsite Interview: Meet with the local team and take a tour of our office for a final meet-and-greet. 
• Finals Steps: Receive feedback and, if successful, an offer! 

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!