SENIOR DATA SCIENTIST JOB SPECIFICATION

We believe in better. And we make it happen.
Better content. Better products. And better careers.
Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.
We turn big ideas into the products, content and services millions of people love.
And we do it all right here at Sky.

ABOUT US

Join us to rethink how sports are experienced. Backed by our new AI-driven platform, we will be building live sports experiences to be more immersive, more personalised - giving fans a chance to take control, watch the game from new angles, even participate in the action, on any device. As a Senior Data Scientist, you’ll work within a specialised machine learning team to build cutting-edge capabilities of the AI-driven platform.
We work in a fast-paced, exploratory environment where ideas are rapidly prototyped, tested, and refined. It’s a space that rewards creativity, flexibility, and a hands-on approach. If you enjoy working iteratively, experimenting with new techniques, and solving open-ended problems, you’ll feel right at home. If not, this may not be the right fit - and that’s okay too.

The Senior Data Scientist will be responsible for developing and implementing data-driven solutions to deliver new innovative sports focussed products to our significant customer base of sports fans. They will be able to identify trends in large datasets and develop models that can predict future outcomes. Additionally, they must be comfortable working with stakeholders across the Organisation to ensure their insights are effectively communicated and implemented.

Responsibilities :

• Develops predictive models using advanced statistical techniques such as regression, classification, clustering, etc.
• Analyses large datasets to uncover patterns and relationships between variables.
• Collaborates with stakeholders across the Organisation to understand their needs and develop appropriate solutions based on data analysis results.
• Own the full lifecycle of ML solutions - designing, deploying, and maintaining models in production environments.
• Monitors performance of existing models over time and adjust parameters accordingly for optimal results.
• Stays up-to-date on industry trends related to data science technologies and best practices in order to recommend new approaches when necessary.
• Build and integrate cloud-native components to expose models as scalable endpoints and publish inference results as events for downstream systems.
• Establish and maintain robust MLOps practices, including CI/CD pipelines, monitoring, retraining strategies, and automated testing.
• Mentor and guide junior data scientists and engineers on best practices for productionising machine learning.

What you’ll bring

• A strong collaborative mindset, with the ability to work across disciplines and contribute creatively
• Have a good understanding of large language and multi-modal models.
• Good experience in Python, Docker and developing in a cloud-based environment (ideally AWS)
• A strong background in data analysis and machine learning, with proven experience, ideally 3 yrs+ architecting and building end-to-end ML systems for industry problems
• AWS Machine Learning Certification desirable
• Experi e nce using Infrastructure-as-Code to deploy ML solutions on AWS