Senior Data Scientist ML Engineer (Forecasting) | NDA

GT was founded in 2019 by a former Apple Nest and Google executive. GTs mission is to connect the worlds 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.

Were 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.

• 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

• 4 years of commercial experience in Data Science / Machine Learning

• Hands-on experience with:

  • Databricks

  • Notebooks

  • PySpark

  • Workflows

  • Deployment through Asset Bundles

• Proven experience building deploying and maintaining production ML solutions

• Broad experience across multiple ML domains including:

  • Forecasting / Time-Series Modelling

  • Regression

  • Classification

  • Gradient Boosting models (e.g. XGBoost LightGBM)

• 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

• Retail or similar consumer-facing industry experience

• Azure DevOps:

  • Repos

  • Boards

  • Pipelines

• 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)

• 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

1. GT interview with Recruiter

2. Technical interview

3. Cultural fit interview

4. Final interview

5. Reference check

6. Security check

Required Experience:

Senior IC