Overview

Stats Perform is the market leader in sports tech. We provide the most trusted sports data to some of the world's biggest organizations, across sports, media, and broadcasting.

Through the latest AI technologies and machine learning, we combine decades' worth of data with the latest in-game happenings. We then offer coaches, teams, professional bodies, and media channels around the world, access to the very best data, content, and insights. In turn, improving how sports fans interact with their favorite sports teams and competitions.

How do they use it?

• Media outlets add a little magic to their coverage with our stats and graphics packages.
• Sportsbooks can offer better predictions and more accurate odds.
• The world's top coaches are known to use our data to make critical team decisions.
• Sports commentators can engage with fans on a deeper level, using our stories and insights.

Anywhere you find sport, Stats Perform is there. However, data and tech are only half of the package. We need great people to fuel the engine.

We succeeded thanks to a team of amazing people. They spend their days collecting, analyzing, and interpreting data from a wide range of live sporting events. If you combine this real-time data with our 40-year-old archives, elite journalists, camera operators, copywriters, the latest in AI wizardry, and a host of 'behind the scenes' support staff, you've got all the ingredients to make it a magical experience!

Our teams of technical experts specialize in harnessing live sporting data, using advanced cloud technologies, Java, JavaScript and Python. It is these tech teams that enable us to extract patterns through AI and Machine Learning and deliver our insights via APIs. In short, they turn complex data into magical experiences with cutting-edge technology.

Responsibilities:

We are looking for a MLOps Engineer (Python + AWS) for our ML Platform team to help build services, tools and processes to maximize speed of ML models delivery.
ML Platform team is maintaining various components of the machine learning services within an organization. Its primary focus revolves around three key areas:

• model registry and experiments tracking,
• real-time model serving,
• cloud training infrastructure.
• ML Platform provides full lifecycle management for dozens of ML models across various sports (Soccer: Live Win Probability, Season Simulation, Player and Team props, xG, PV/Momentum, Power Rankings, Opta Vision; Cricket, Basketball, American Football, Tennis: Live Win Probability, Season Simulation; …).

As an experienced/senior engineer you will be expected to work independently, help solve technical challenges, and be an example in following best practices.

• Develop and deploy tools and services for machine learning inference (real-time) and training (Python, AWS, Terraform, CI/CD Jenkins, Kubernetes, ML flow).
• Work together with AI/DS team to help train and productionize new ML models.
• Work on Model Cards and Model Catalogue.
• Drive changes to ML project model lifecycle according to MLOps & Engineering best practices.
• Acquire expertise in sports data, including live event data, tracking data, player statistics, tournaments, and schedules for various sports.
• Refactor and optimize for production PoCs created by AI/DS team.
• Design and implement libraries, which can be used by other teams (Python).
• Use logging and monitoring tools to ensure availability end-to-end observability.
• Engage in technical design discussions within the engineering teams and other senior engineers in the organization.

Required Qualifications:

• Experience with Python.
• Knowledge of ML lifecycle management tools and platforms: MLFlow, Weights and Biases.
• Experience with data/feature engineering.
• Knowledge of Machine Learning.
• Knowledge of sports data domain or desire to learn it.
• Experience with Py Torch.
• Experience deploying AWS Cloud Infrastructure (Terraform, CloudFormation, CDK) or any other public cloud.
• Bachelor’s degree in computer science or similar
• Verbal/written communication and presentation skills, including the ability to effectively communicate with both business and technical teams, and both internal and external stakeholders.
• An open-minded, structured thinker, a team player and a good teammate
• Intellectual curiosity and excellent problem-solving skills, including the ability to structure and prioritize the approach for maximum impact.

Desired qualifications:

• Knowledge of Data Science.
• Experience with SQL and NoSQL databases.
• Experience with event-driven, messaging, distributed systems.
• Knowledge of ML Monitoring tools and platforms: Evidently, Why Logs.
• Knowledge of Feature Stores
• Experience in building MLOps infrastructure for inference and training.
• Experience with Python data libraries (Pandas, SciPy, NumPy)
• Experience with ML Frameworks (Py Torch, TensorFlow, sklearn)
• Experience with solution architecture and system design.
• Experience with Docker (or other containers).
• Experience with generic logging and monitoring frameworks (ELK, Prometheus, Grafana).
• Experience with AWS streaming services, e.g. MSK (Kafka), Kinesis.
• Experience with AWS microservices capabilities, e.g. Lambda, SNS, SQS.
• Experience with AWS data services, e.g. DynamoDB, S3, Redshift.

Why work at Stats Perform?

We love sports, but we love diverse thinking more!

We know that diversity brings creativity, so we invite people from all backgrounds to join us. At Stats Perform you can make a difference, by using your skills and experience every day, you'll feel valued and respected for your contribution.

We take care of our colleagues

We like happy and healthy colleagues. You will benefit from things like Mental Health Days Off, ‘No Meeting Fridays,’ and flexible working schedules.

We pull together to build a better workplace and world for all.

We encourage employees to take part in charitable activities, utilize their 2 days of Volunteering Time Off, support our environmental efforts, and be actively involved in Employee Resource Groups.

Diversity, Equity, and Inclusion at Stats Perform