Data Scientist (AI/ML)

Forward Role; Cheltenham; On-site; GBP 50,000 - 85,000; Full time

Job summary

Forward Role is facilitating a Data Scientist (AI/ML) role focused on turning ML models into live systems for government-facing programs. You will join a small, cross-disciplinary team including data and software engineers and end users to ensure real-world impact.

You’ll shape AI/ML strategy, work closely with customers, and influence how models are built, validated and deployed in secure environments.

Qualifications

• Experience with Python-based data science and ML, including NLP or graph analytics.
• Comfortable with sensitive data and working in a security-focused environment.
• Able to explain complex analysis to non-specialists.

Responsibilities

• Develop ML and NLP models for intelligence data, including pattern detection and data matching.
• Automate triage and analysis of large, multi-source datasets (sensor, geospatial, comms).
• Build production-grade data and ML pipelines; deliver dashboards/tools for non-technical users.

Skills

Python

Pandas

scikit-learn

PyTorch

TensorFlow

NLP

Graph analytics

Spark

AWS

Tools

Spark

AWS

Pandas

scikit-learn

PyTorch

TensorFlow

Job description

Data Scientist (AI/ML)

Location: London, Surrey, Cheltenham or Manchester
Clearance: Active eDV Clearance Required
Salary: £50,000-£85,000 per annum + DV Bonus

If you're tired of building models that never leave the notebook, this one goes live.

You'd join a specialist security and intelligence consultancy that works on live government programmes, putting ML into operational systems that analysts and mission teams use every day. You'll sit in a small, multi-disciplinary agile team with data engineers, software engineers and the end users themselves, so you see what your work changes.

You won't be "the data person" bolted onto someone else's delivery team. You'll help shape the AI/ML approach, get close to the customer, and have a say in how models are built, validated and deployed in secure environments.

What you'll be working on

• ML and NLP models for intelligence data: pattern detection, data matching, anomaly spotting
• Automated triage and analysis of large, messy, multi-source datasets (sensor, geospatial, comms)
• Graph analytics and time-series work
• Data and ML pipelines built for production, not demos
• Dashboards and tools that non-technical users can act on
• Python (Pandas, scikit-learn, PyTorch/TensorFlow), Spark and AWS

Why it's worth a look

• Real operational deployment, not endless proofs of concept
• Direct contact with the people using what you build
• Room to lead on AI/ML strategy and best practice as you grow

Must have:

• Experience of Python-based data science and ML, and some exposure to NLP or graph analytics.
• Comfortable with sensitive data.
• Able to explain complex analysis to non-specialists.