Senior Data Scientist / ML Engineer (Forecasting) | NDA
UK - Hybrid · 4+ years experience · Contract · Hybrid · Posted Oct 5, 2026
At a glance
- Experience
- 4+ years experience
- Employment
- Contract
- Workplace
- Hybrid
- Location
- UK - Hybrid
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.
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
Requirements
- 4+ years of commercial experience in Data Science / Machine Learning
- Hands-on experience with Databricks, Notebooks, PySpark, Workflows, and 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, and 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
Preferred qualifications
- 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)
Workplace
- Office attendance: up to 3 days per week in the Nottingham office.
Skills
- Databricks
- PySpark
- Prophet
- ARIMA
- LSTM
- TimeGPT
- XGBoost
- LightGBM
- Python
- Pandas
- NumPy
- Scikit-learn
Show all 15 skills
- PyTorch
- Git
- SQL
