Data Scientist
Posted 5 Oct 2026
Advertised as “Senior Data Scientist / ML Engineer (Forecasting) | NDA”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 4+ yrs
- Management level
- Individual contributor
- Employment
- Hybrid
- Contract
- Contract
No salary listed for this role.
GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.
Our clients operate in industries like healthcare, life sciences, fintech, retail, e-commerce, finance and many more - giving our team exposure to real-world, high-impact projects.
About the Role
We’re looking for a Senior Data Scientist / ML Engineer to join a UK-based client in the healthcare and pharmacy domain.
The role combines forecasting and machine learning with end-to-end ownership of solution delivery, from project discovery and stakeholder collaboration through model development, deployment, and productionisation.
Location: Nottingham, UK
Office attendance: up to 3 days per week in the Nottingham office.
Project Details:
The project focuses on developing a forecasting solution for a large healthcare network.
It uses historical clinic and marketing data to predict clinic usage and staffing needs, helping optimize scheduling and resource allocation.
The goal is to build a scalable, data-driven platform that improves operational efficiency.
Responsibilities:
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Design, train, and deploy ML models for time-series forecasting and related data tasks
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Build and maintain data pipelines using cloud-native tools (AWS, GCP, or Azure)
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Develop and optimize forecasting models (Prophet, ARIMA, LSTM, TimeGPT)
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Collaborate with data, product, and cloud engineers to deliver reliable, scalable solutions
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Participate in different stages of the project lifecycle - from discovery and PoC to production deployment, presenting your work to stakeholders
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Work closely with business stakeholders and SMEs to gather requirements, shape solutions, and drive project discovery
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Communicate modelling approaches, assumptions, and results to both technical and non-technical audiences
Essential knowledge, skills & experience (must-have):
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4+ years of commercial experience in Data Science / Machine Learning