Department: Product Incubator
Job Title: Data Scientist III (m/f/d)
Reports To (title): Chief Innovation Officer
Location: Austria - Graz / Remote
Stats Perform collects the richest sports data in the world and transforms it through revolutionary artificial intelligence (AI) to unlock the most in-depth insights for media and technology, betting and team performance. With company roots dating back almost 40 years, Stats Perform embraces and solves the dynamic nature of sport – be that for digital and broadcast media with differentiated storytelling, tech companies with reliable and fast data to power their own innovations, sportsbooks with in-play betting and integrity services, or teams with first-of-its-kind AI analysis software. As the leading sports data and AI company, Stats Perform works with most of the top global sports broadcast companies, tech companies, sportsbooks, teams and leagues.
Do you have a background in Data Science, Machine Learning, Computer Vision, Physics, Statistics or Probability Theory? Do you have a passion for sports? Do you live to find data driven solutions to complex problems? Come join our team at Stats Perform as a Data Scientist building predictive models with modern deep learning tools that will be utilized by the world’s leading technology companies, sports franchises and sports book operators.
The role is part of the Product Incubator with the purpose to bring new models & products to market at a fast pace. You will be part of a dynamic team which will work on solving complex problems by creating cutting edge models based on unique data sets, work with a team on launching the initial product, transition it into the product engineering function and move on to the next challenge.
WHAT’S YOUR NEW ROLE ABOUT?
- Researching, developing, and implementing the most innovative machine learning and computer vision techniques to Stats Perform’s wealth of sports data (both structured and unstructured) with a specific focus on Tennis data
- Productizing artificial intelligence-based solutions alongside engineers and product teams
- Providing technical guidance to product teams on the artificial intelligence (machine learning and computer vision) approaches appropriate for a task
- Patenting the innovative solutions
- Lifecycle and collaboration with our teams:
- Machine Learning lifecycle: data prep, training data generation, feature engineering, optimization, experimentation, reproducibility, deployment, and end-to-end workflow management
- Partners and stakeholders: identify data acquisition opportunities, create requirements, transform large volume data into AI-ready high-quality relevant datasets
- Accelerate the velocity from idea to interference into production
- Achieve quality ML data using a triad of people, process & technology
- Conduit between Product and Data Engineering to bring new models into production in a quick and efficient way
- Support, train and mentor team members on best ML implementation practices
- ML and Deep Learning capabilities at vast scale by developing the necessary systems, tools, technologies and integrations as part of the ML Platform offering
Our team members typically have:
- 3+ years of relevant industry experience in data & analytics platform or machine learning and data science
- Hands on experience with building enterprise grade machine learning and data platforms
- Familiarity with common machine learning algorithms (random forest, XGBoost, etc.)
- Familiarity with advanced ML techniques (neural networks/deep learning, reinforcement learning, active learning, data augmentation and GAN etc.)
- Experience with high-level programming languages and big data tools and ecosystems
- In-depth working knowledge of cloud infrastructure such as AWS or Google Cloud
- Proficiency in, at least, one modern deep learning engine such as Tensorflow, PyTorch etc. (preferred: knowledge of using GPUs)
- Knowledge of Spark or advanced ETL skills dealing with real-time stream processing
- Experience in integrating with internal and external complex systems that are able to scale and demonstrate security, reliability, scalability, and cost-efficiency
- Experience in projects involving large scale multi-dimensional datastore, complex business infrastructure, and cross-functional teams, and track record of successfully launched ML projects in production
- Passion for creating new technologies with high product impact within sport.
- Bachelor’s, MS or PhD in Computer Science, Mathematics, Computational Statistics, Machine Learning or related STEM fields
- Verbal/written communication and presentation skills, including an ability to effectively communicate with both business and technical teams, and both internal and external stakeholders
- An open-minded, structured thinker