Sportradar
Data Scientist
Job Description
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
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
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, will understand methods for rigid validation of results, and master different statistical analysis tools and scripting to develop and validate models and data analysis ideas.
THE CHALLENGE:
- Analyse and explore data using statistical analysis tools and scripting
- Develop machine learning or statistical predictive models for use in our products and services
- Rigorously validate methods, models, algorithms and hypotheses using back-testing on historical data and/or simulations
- Design and implement novel methods for data analysis, tailored to our sports-related application domains
- 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 in our integrity services product vertical
- Present ideas and solutions to software developers and business stakeholders in a clear and understandable way
YOUR PROFILE:
- Demonstrated competency in the following areas: machine learning and/or statistics, efficiently working with big data, statistical validation of results
- Work experience in data science, statistical modelling, applied mathematics and/or software engineering roles.
- Experience with Python, R or similar statistical and/or machine learning software/toolkits
- Programming experience is a must
- Proficiency with advanced querying of large analytical databases using SQL.
- Experience working with Mac/Linux environments is a plus
- Experience working in Java is a plus
- Hands-on experience with big data frameworks (Spark, Flink, Spark) and/or cloud solutions (AWS S3, Redshift, Athena, EMR) is a plus
- Hands-on experience with developing reporting solutions and interactive dashboards using BI tools such as Qlik Sense, Tableau or PowerBI is a must
- Web Scraping is a plus
- Knowledge of APIs is a plus
- 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
- Anomaly detection expert with a curious mind, to combat financial fraud in sports betting industry
- Interested in sport
OUR OFFER:
- Competitive salary and benefits.
- Work in an international team collaborating with colleagues from all over the world.
- Opportunity to work and develop in a dynamic Tech environment within an inspiring and fast-growing company.
- A challenging but rewarding and fun environment.
Additional Information
Sportradar is an Equal Opportunity Employer. We are committed to encourage diversity within our teams. All qualified applicants will receive consideration without regard to among other things, your background, status, or personal preferences
