TieTalent Waltham Abbey, England, United Kingdom
Senior Data Scientist
We believe in better. And we make it happen. We turn big ideas into products, content and services that millions love. 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 across devices. 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 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.
What you'll do
The Senior Data Scientist will be responsible for developing and implementing data-driven solutions to deliver new innovative sports-focused products to a large customer base of sports fans. You will identify trends in large datasets and develop models that can predict future outcomes. You must be comfortable working with stakeholders across the organisation to ensure insights are effectively communicated and implemented.
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 performance of existing models over time and adjust parameters for optimal results.
* Stay up-to-date on industry trends related to data science technologies and best practices.
* 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 collaborative mindset with the ability to work across disciplines and contribute creatively.
* Understanding of large language and multi-modal models.
* Strong experience in Python, Docker and cloud-based environments (ideally AWS).
* Background in data analysis and machine learning with proven experience (ideally 3+ yrs) architecting and building end-to-end ML systems.
* 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
* A generous pension package
* Private healthcare
* Discounted mobile and broadband
* A wide range of Sky VIP rewards and experiences
Inclusion & how you'll work
We are a Disability Confident Employer and welcome applications from all candidates. We will ensure a fair and consistent experience and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can. We’ve embraced hybrid working and split our time between office spaces and working from home.
Your office space
Osterley – Our Osterley Campus is a short walk from Syon Lane train station. Free shuttle buses run to Osterley, Gunnersbury, Ealing Broadway and South Ealing. On campus you’ll find restaurants, a gym, cinema, and other facilities.
In addition, if your application is successful, you may be asked to complete a criminal record check. Depending on the role and the nature of any convictions, we might withdraw the offer.
We’re committed to keeping applications up-to-date. If your application is not successful, you may be contacted about other opportunities.
Note: This posting is for a role based in Waltham Abbey, England. If you believe you have the right to work in the UK, please apply.
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