Computer science msc Work, Jobs in London, Eng (with Salaries)

Data Scientist — Data Engineering & Applied AI
Nationwide Utilities —London
- £36,500 a year
- Part-time
- Computer Science
- Engineering
- No experience needed
Quick apply
11d
Data Science and AI Trainer (Government)
QA —London
- Azure
- Doctoral degree
- Computer Science
- Annual leave
- Employee assistance programme
Data & AI Trainer
QA —London
- Azure
- Doctoral degree
- Computer Science
- Annual leave
- Employee assistance programme
Research Assistant
University College London —London
- £39,148 a year
- Full-time
- Hybrid work
- Master's degree
- Machine learning
- Communication skills
- Annual leave
- Employee assistance programme
12d
Taught Programmes Officer
Imperial College London —South Kensington
- £41,005 - £45,616 a year
- Full-time
- Computer Science
- Customer service
- Microsoft Office
5d
Summer Intern Systems Development
SS&C Technologies —London
- Full-time
- Hybrid work
- Doctoral degree
- Java
- Analysis skills
Software Engineer (Python / ETL) - London
Validus Risk Management —London
- Hybrid work
- Data analysis skills
- Master's degree
- Maths
Quick apply
Research Technician
University College London —London
- Full-time
- Computer Science
- Engineering
- Java
- Annual leave
- Employee assistance programme
2d
Associate Quantitative / Systematic Researcher
Aviva —London
- Part-time
- Doctoral degree
- Master's degree
- Machine learning
- Employee discount
11d
Lecturer (Teaching) in Software Systems, Artificial Intelligence and Data Engineering
University College London —London
- £54,931 - £64,644 a year
- Full-time
- Engineering
- Bachelor's degree
- Teaching
- Annual leave
- Employee assistance programme
2d
Full-time PhD studentship (Chain & Yong Group)
University College London —London
- £24,643 a year
- Full-time
- Computer Science
- Master's degree
- Maths
3d
Software Engineer, Trading Connectivity, London
Talos Global —London
- Full-time
- Computer Science
- Engineering
- No experience needed
- Annual leave
- Employee stock ownership plan
Machine Learning Researcher - Apple Music - Recommender Systems
Apple —London
- Doctoral degree
- Computer Science
- Master's degree
12d
Software Engineer - Applications
vServices —London
- Master's degree
- Bachelor's degree
- Linux
Quantitative Analyst – Execution Research
Smartodds —London
- Full-time
- Doctoral degree
- Master's degree
- SQL
- Employee assistance programme
- Employee discount
Quick apply
CHAI Research Fellow
University College London —London
- £43,981 - £52,586 a year
- Full-time
- Doctoral degree
- Computer Science
- University
- Annual leave
- Employee assistance programme
Principal Data & AI Trainer
QA —London
- Azure
- Doctoral degree
- Computer Science
- Annual leave
- Employee assistance programme
2d
Machine Learning Engineer
PlayStation Global —London
- Hybrid work
- Doctoral degree
- Computer Science
- Engineering
Lecturer (Teaching) in IoT & System Engineering
University College London —London
- £54,931 - £64,644 a year
- Full-time
- Doctoral degree
- Computer Science
- Engineering
Venture Capital Investor
Merantix —London
- Doctoral degree
- Computer Science
- Master's degree
Quick apply

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Data Scientist — Data Engineering & Applied AI

Nationwide Utilities -
London

Quick apply

Job details

Permanent | Part-time | Full-time
£36,500 a year
11 days ago

Qualifications

Law
Computer Science
PyTorch
Engineering
NumPy
R
Mathematics
No experience needed
English
Master's degree
SQL
Pandas
Analysis skills
Docker
Bachelor's degree
Machine learning
SciPy
APIs
IT
Linux
Data science
AI
Business
Communication skills
Python

Full job description

"Energy is one of the defining industries of our time central to the global economy, the climate transition, and the future of technology." Alex Pinna - Founder and CEO

Company Overview

Nationwide Utilities is on a mission to simplify the world of energy procurement, making it hassle-free and cost-effective for businesses across various industries. With 25 years of industry experience, our dedicated team of experts is passionate about helping businesses find the perfect energy solutions that align with their unique needs and financial goals.

Job Description

We sit right at that crossroads, helping some of the UK and Europe’s biggest energy users make smarter, greener, and more commercially sound decisions. With over two decades of industry heritage and the momentum of a high-growth scale-up, we’re investing heavily in our next chapter: AI-powered tools, data-driven systems, automation, and strategic expansion across European markets.

We’re also training every member of our team to harness AI in their own workflow turning insight into action faster and smarter. If you want to apply data science, engineering and AI to real-world commercial and operational problems in one of the world’s most important sectors, this could be your opportunity.

About the role

We’re looking for a technically strong and practical Data Scientist Data Engineering & Applied AI to support the development of our data, automation and applied AI capabilities.

This is not a conventional data analyst role. The focus is on preparing, structuring and improving data so it can be used reliably for reporting, automation, forecasting, machine learning and future AI-enabled systems. You’ll work across data engineering and applied data science, helping to build reusable datasets, improve data quality, create repeatable workflows, and support practical technical solutions across the business.

This role would suit a graduate or early-career candidate with strong Python, SQL and data science skills who wants to work on real business problems and grow into a broader data, AI and machine learning role. You do not need to be an energy expert from day one, but you should be curious, technically capable, and motivated to learn how data and AI can be applied in the energy and utilities sector.

Why this role matters

Data is becoming central to how modern businesses operate, make decisions and build intelligent systems.

At Nationwide Utilities, we are developing stronger data foundations to support better analysis, smarter automation, forecasting, internal tools and AI-enabled workflows.

This role is important because good data makes everything else possible: clearer reporting, better decisions, more useful automation, stronger forecasting and more reliable AI systems.

You’ll help build the practical data foundations that support the next phase of our growth.

What you'll be doing

Collecting, cleaning, transforming and standardising datasets from approved business and market sources
Creating reusable datasets for analysis, reporting, automation and machine learning
Building repeatable data workflows using Python, SQL, APIs and related tools
Supporting schema design, data validation and documentation
Working with technical, operational and commercial teams to understand data requirements
Preparing reliable datasets for forecasting, anomaly detection and applied machine learning
Supporting internal tools, dashboards and AI-assisted workflows
Helping improve data quality, consistency and accessibility across the business
Communicating technical findings clearly to non-technical colleagues

What we're looking for

Strong Python skills, especially for data work
Good SQL knowledge
Experience cleaning, transforming and analysing datasets
Understanding of structured data, data quality and validation
Ability to work with data from different sources and formats
Strong analytical and problem-solving skills
Good attention to detail
Clear communication skills and ability to explain technical work in plain English
Interest in data engineering, machine learning and applied AI
Willingness to learn about energy, utilities and commercial data
A practical mindset focused on building useful and reliable systems

Useful skills and experience

The following would be useful, but not all are required:

Pandas, NumPy, SciPy
Matplotlib, Seaborn or other visualisation tools
scikit-learn, XGBoost or PyTorch
R
APIs and ETL workflows
Database design
Cloud platforms, Linux or Docker
Time-series analysis
Forecasting
Anomaly detection
Machine learning pipelines
LLM or AI workflow experience

Ideal backgroud

This role is well suited to someone with:

MSc in Data Science, Computer Science, AI, Statistics, Mathematics, Engineering or a related subject
Undergraduate degree in Mathematics, Computer Science, Engineering, Physics, Statistics or another quantitative field
Graduate or early-career experience in data science, data engineering, analytics or machine learning
Academic or project experience working with real-world datasets
Previous energy sector experience is not required, but an interest in energy, utilities, markets, forecasting or commercial data would be helpful.

Option to work part-time if candidate is currently still in education, salary will be prorated accordingly.

Pay: £36,500.00 per year

Application question(s):

Tell us about a data project where you collected, cleaned, structured or transformed data into something useful. What was the problem, what did you build, and what was the result?
This role involves building reliable data foundations for analytics, automation, forecasting and AI. What interests you most about that kind of work, and what skills or experience would you bring to it?

Work Location: In person

Quick apply

Refine Your Search

computer science msc jobs in london, eng

Data Scientist — Data Engineering & Applied AI

Data Science and AI Trainer (Government)

Data & AI Trainer

Research Assistant

Taught Programmes Officer

Summer Intern Systems Development

Software Engineer (Python / ETL) - London

Research Technician

Associate Quantitative / Systematic Researcher

Lecturer (Teaching) in Software Systems, Artificial Intelligence and Data Engineering

Full-time PhD studentship (Chain & Yong Group)

Software Engineer, Trading Connectivity, London

Machine Learning Researcher - Apple Music - Recommender Systems

Software Engineer - Applications

Quantitative Analyst – Execution Research

CHAI Research Fellow

Principal Data & AI Trainer

Machine Learning Engineer

Lecturer (Teaching) in IoT & System Engineering

Venture Capital Investor

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