Data Science & Software Placement Year Student

Frazer-Nash Consultancy
Manchester
2 months ago
Applications closed

Related Jobs

View all jobs

Trainee Patent Attorney – AI & Machine Learning

Trainee Patent Attorney – AI & Machine Learning

Trainee Patent Attorney – AI & Machine Learning

KTP Associate – Computer Vision & Machine Learning Engineer

Data Scientist - Level 1

Scientist, Data Science

Data Science & Software Placement Year Student

Title: Data Science & Software Placement Year Student


Locations: Bristol, Burton, Leatherhead, Manchester and Gloucester


Start Date: 29th June 2026


Closing Date: 11th January 2026 (rolling deadline, early applications encouraged)


Contract Length: 10-12 months


Who We Are: Frazer-Nash are an engineering, systems and technology consultancy.


Through our meaningful innovations, our experts support organisations make lives safe, secure, sustainable and affordable.


Why Frazer-Nash: The world and our clients have lots of problems and we get a kick out of finding digital and data solutions to these problems. As a Placement year student, you will typically be working on multiple projects simultaneously, managing your time and accruing a wealth of experience and skills.


The role: This is a Data Science and Software Engineer placement year role within our Digital stream at Frazer-Nash. As a student you could be joining one of our Data Science teams, which cover the full data life cycle from data governance to analytics, forecasting to decision making, or one of our Engineering Software teams, which cover the full software design life cycle from requirements and specification through design and implementation to testing.


Our teams deliver engineering solutions through system architecture, modelling, custom software and strategic advice across all our markets, including defence, energy, transport, government and others.


We are looking for enthusiastic, open and curious minded people who enjoy problem solving. Those selected will receive training, mentoring and coaching to support their development into becoming well-rounded consultants and will be supported to achieve professional accreditations including chartership.


We’re Looking For People Who Can Become:



  • A creator: Our projects solve problems that customers have today, some of these turn into solutions that we can re-use as products. You will have the vision for how to re-use your work to solve bigger problems in the future. Given a blank sheet of paper we are looking for candidates who are able to create the new and the different.
  • A collaborator: You will work in multi-disciplinary teams with other Frazer-Nash colleagues and our customers. You will be able to get along with others from different technical and social backgrounds and be part of a team which is more capable than the sum of its parts.
  • An adapter: Ability to adapt to different and complex situations and manage your time to meet competing demands.
  • A multi-tasker: You will work on multiple projects concurrently and quickly take responsibility for delivery of different elements. Your responsibilities will grow year-on-year, as you grow in capability. You will have the ability to manage your own time to handle competing demands to meet deadlines.
  • A problem solver: You will solve many different technical problems, seeing them from different perspectives and finding solutions which put the customer at the heart of our work. Often our clients aren’t aware of what outcomes best suit their requirements. You will have the ability to explore different options for our clients to ensure we deliver the best outcomes.

Eligibility: You will be on track to obtain a 2:1 Degree or higher (or equivalent/experience) with a related Engineering, Computer Science, Maths or Physical Sciences bias.


Pre-employment screening and satisfaction with UK National Security Vetting clearance criteria are required.


Our Recruitment Process:



  1. Application - CV submission
  2. Measure Potential - Arctic Shores task-based assessment
  3. Video Interview - Situation based & technical questions
  4. Explore Interview – virtual/in-person interview with competency and technical questions
  5. Decision/Feedback – you receive feedback regardless of outcome

Benefits and Offerings:



  • The opportunity to join and learn with a team that’s both enthusiastic and encouraging.
  • An attractive salary: £25,000 pro rata
  • 25 days holiday + the opportunity to buy 5 days.
  • Company pension scheme.
  • Private healthcare membership + wellbeing support.
  • Bonus scheme linked into company performance.
  • Support and mentoring on route to achieving professional accreditation.
  • Paid membership fees to a professional institution.
  • Early career teams and office socials.

Equal Opportunities: Individuals from diverse backgrounds are encouraged to apply, as we believe that diversity and inclusion are fundamental to creating a dynamic and thriving workplace culture.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.