Senior Data Scientist / ML Engineer (Forecasting) | NDA

GT; High Wycombe; Hybrid; GBP 75,000 - 110,000; Full time

Job summary

GT is seeking 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. Project duration: 6 months with potential extension.

Qualifications

• 4+ years of commercial experience in Data Science / Machine Learning.
• Hands-on experience with building, deploying, and maintaining production ML solutions.
• Broad experience across multiple ML domains, including forecasting and modeling.
• Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch) and SQL.
• Experience with cloud environments (Azure preferred, AWS/GCP also considered).
• Fluent English communication and collaboration with stakeholders.

Responsibilities

• Design, train, and deploy ML models for time-series forecasting.
• Build and maintain data pipelines using cloud-native tools (AWS, GCP, or Azure).
• Develop and optimize forecasting models (Prophet, ARIMA, LSTM, TimeGPT).
• Collaborate with data, product, and cloud engineers to deliver scalable solutions.

Skills

Python

Time-series forecasting

Production ML

Cloud computing

Stakeholder management

Communication

Tools

Azure

AWS

GCP

Databricks

Weaviate

Milvus

Job description

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 duration : 6 months (with possible extension).

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:

• Design, train, and deploy ML models for time-series forecasting and related data tasks
• Build and maintain data pipelines using cloud-native tools (AWS, GCP, or Azure)
• Develop and optimize forecasting models (Prophet, ARIMA, LSTM, TimeGPT)
• Collaborate with data, product, and cloud engineers to deliver reliable, scalable solutions
• Participate in different stages of the project lifecycle - from discovery and PoC to production deployment, presenting your work to stakeholders
• Work closely with business stakeholders and SMEs to gather requirements, shape solutions, and drive project discovery
• Communicate modelling approaches, assumptions, and results to both technical and non-technical audiences

Essential knowledge, skills & experience (must-have):

• 4+ years of commercial experience in Data Science / Machine Learning
• Hands-on experience with:
• Proven experience building, deploying, and maintaining production ML solutions
• Broad experience across multiple ML domains, including:
• Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch)
• Experience with model evaluation, performance monitoring, and accuracy metrics
• Version control (Git)
• Experience working with cloud environments (Azure preferred, AWS/GCP also considered)
• SQL
• Fluent English

Nice-to-have:

• Retail or similar consumer-facing industry experience
• Azure DevOps:
• Experience with Databricks model training and inference workflows
• Databricks Apps and Lakebase
• Experience with RAG pipelines
• Experience with vector databases (Weaviate, Milvus)
• Familiarity with LLM evaluation frameworks (e.g. DeepEval)

Soft Skills

• Strong sense of ownership and accountability
• Strong stakeholder management skills
• Proactive attitude and ability to work independently
• Clear and confident communication with both tech and non-tech stakeholders
• Comfortable working in ambiguity and helping define requirements
• Strategic thinking and focus on business impact
• Team player

Interview Steps

1. GT interview with Recruiter
2. Technical interview
3. Cultural fit interview
4. Final interview
5. Reference check
6. Security check