Research and modeling: Staying abreast with state of art research literature within machine learning and/or computer vision domains with specific focus on sports. Good understanding of classical and latest techniques in Machine learning and/or computer vision whilst handling time-series, large scale event and tracking datasets. Researching, developing, and implementing the most innovative machine learning and/or computer vision techniques to Stats Perform’s wealth of sports data (both structured and unstructured). Exploring generative AI frameworks for sports-specific applications. Productizing artificial intelligence-based solutions alongside engineers and product teams. 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. Developing good documentation around models, usage and constant engagement with Machine learning engineering team.
Enabling our products: ML and Deep Learning capabilities at vast scale by developing the necessary systems, tools, technologies and integrations as part of the ML Platform offering.
requirements-expected :
Experience of 3+ years of relevant industry experience in data, video & analytics platform related to one of machine learning, computer vision and data science.
Hands on experience with building enterprise grade machine learning and data platforms.
Proficiency in Python and SQL and 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.) and with CNN network development, multi object tracking, re-identification. Optical character recognition etc, for computer vision challenges.
Proficiency in modern deep learning frameworks using Tensorflow, PyTorch etc. (preferred: knowledge of using GPUs).
Appreciation for or experience with real-time performance optimization, including low-level computation techniques.
Knowledge of Spark or advanced ETL skills dealing with real-time stream processing
Understanding of generative AI concepts and techniques such as transformers, diffusion models, Retrieval-Augmented Generation (RAG), prompt engineering and related advancements.
Education: Bachelor’s, MS or PhD in Computer Science, Mathematics, Computational Statistics, Machine Learning or related STEM fields.
Fluency in English; excellent verbal and written communication and presentation skills, including an ability to effectively communicate with both business and technical teams, and both internal and external stakeholders.
offered :
Top-tier private healthcare – Fully covered premium medical care.
Extra vacation days, with more added as your tenure grows.
Mental health days – Company-wide days off to reset and recharge.
Hybrid work flexibility – Because productivity isn’t tied to a desk.
Career & learning support – Access to Udemy, O’Reilly, and other learning platforms to keep your skills sharp.
Diversity, Equity, and Inclusion at Stats Perform
At Stats Perform, diversity drives innovation. We are committed to building an inclusive, welcoming workplace where everyone is valued and respected. Our DEI goals are at the heart of our culture, ensuring we better serve our clients and communities.
