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Overview
Senior Data Scientist role focused on developing and implementing data-driven solutions to deliver innovative sports-focused products for a large sports fan base. Work within a specialised machine learning team to build cutting-edge capabilities of an AI-driven platform in a fast-paced, exploratory environment that rewards creativity and a hands-on approach.
Join us to rethink how sports are experienced. Backed by our AI-driven platform, we will be building live sports experiences to be more immersive and personalised—giving fans new ways to watch and participate on any device. If you enjoy iterating, experimenting with new techniques, and solving open-ended problems, you’ll feel at home.
What you’ll do
The Senior Data Scientist will develop and implement data-driven solutions to deliver new innovative sports-focused products for our substantial customer base. They will identify trends in large datasets and build models that predict future outcomes. They must be comfortable working with stakeholders across the organisation to communicate insights effectively and drive implementation.
Responsibilities
* Develop predictive models using advanced statistical techniques such as regression, classification, clustering, etc.
* Analyse large datasets to uncover patterns and relationships between variables.
* Collaborate with stakeholders across the organisation to understand needs and develop data-driven solutions.
* Own the full lifecycle of ML solutions – designing, deploying, and maintaining models in production.
* Monitor model performance over time and tune parameters for optimal results.
* Stay up-to-date on industry trends and best practices to recommend new approaches.
* 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 productionising machine learning.
What you’ll bring
* A strong collaborative mindset, with the ability to work across disciplines and contribute creatively
* 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
* Experience using Infrastructure-as-Code to deploy ML solutions on AWS
The rewards
* Sky Q, for the TV you love all in one place
* Sky Glass at an exclusive rate
* Generous pension package
* Private healthcare
* Discounted mobile and broadband
* Sky VIP rewards and experiences
Inclusion & how you’ll work
We are a Disability Confident Employer and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.
Hybrid working is embraced, with time split between unique office spaces and working from home. You’ll learn more about what hybrid working looks like for your role later in the recruitment process.
Your office space
Osterley Campus – a 10-minute walk from Syon Lane rail or free shuttle buses to nearby stations, plus bike shelters and showers. On campus you’ll find 13 subsidised restaurants, cafes, and a Waitrose. Facilities include a subsidised gym, cinema, car wash, and beauty salon.
We’d love to hear from inventive, forward-thinking minds in Tech, Product and Data at Sky. We embrace differences, support our community, and contribute to a sustainable future. If you believe in better, we’ll back you all the way.
Just so you know: if your application is successful, we’ll ask you to complete a criminal record check. Depending on the role and any convictions, we might withdraw the offer.
Note: Some content in the original description (other job postings and extraneous lines) has been omitted for clarity and relevance to this role.
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