Senior Data Scientist | Time-Series Forecasting & ML Ops

Gt Hq; Nottingham; Hybrid; GBP 65,000 - 95,000; Full time

Job summary

GT is seeking a Senior Data Scientist / ML Engineer for a UK-based healthcare project in Nottingham. You will own end-to-end delivery from discovery to deployment, designing forecasting solutions and ML models that optimize clinic staffing and scheduling.

The role emphasizes collaboration with business stakeholders, data and cloud engineers, and SMEs, with hybrid office attendance up to 3 days per week in the Nottingham office. The project lasts 6 months with possible extension.

Qualifications

• 4+ years of commercial experience in Data Science / Machine Learning.
• Experience building, deploying, and maintaining production ML solutions.
• Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch).

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.

Skills

Data Science

Machine Learning

Time-Series Forecasting

Python

Pandas

NumPy

scikit-learn

PyTorch

XGBoost

LightGBM

Databricks

PySpark

Git

SQL

Azure

AWS

GCP

Tools

Databricks

Notebooks

PySpark

Asset Bundles

Databricks Apps

Lakebase

RAG pipelines

Weaviate

Milvus

Job description

GT is seeking a Senior Data Scientist / ML Engineer for a UK-based healthcare project in Nottingham. You will own end-to-end delivery from discovery to deployment, designing forecasting solutions and ML models that optimize clinic staffing and scheduling.

The role emphasizes collaboration with business stakeholders, data and cloud engineers, and SMEs, with hybrid office attendance up to 3 days per week in the Nottingham office. The project lasts 6 months with possible extension.