Human Factors Engineer

Gaydon
9 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist, United Kingdom - BCG X

Manager Quantitative Analysis - Centre for UK Growth

Data Scientist, United Kingdom - BCG X

Manager Quantitative Analysis - Centre for UK Growth

Manager Quantitative Analysis - Centre for UK Growth

Data Scientist, United Kingdom - BCG X

Our OEM Client based in Coventry, is searching for a Human Factors Engineer to join their team, Inside IR35. This is a 12-month contract position initially until 31st March 2026, with the potential for further extensions.

Umbrella Pay Rate: £27.03.

We are seeking a highly motivated and skilled Human Factors Researcher to join the Human Sciences team.

The team is made up of Human factors researchers, psychologists and cognitive neuroscientists.

This role exists to create human centred user experience design for future products. This centres around the conception and design of user interface systems for the vehicle (including but not limited to, centre screen, voice, passenger entertainment and control screens, and any other appropriate interaction method).

Taking on requirements for the general principles of operation, as well as the information requirements of the system being developed then proposing appropriate content design schemes for use in the next gen in-vehicle systems.

Working within an automotive field requires consideration of the impact of in-vehicle systems on the driving task and hence designing systems that support a driver to carry out this task is the primary aim. 

The ideal candidate will have a strong background in human factors, ergonomics, and user experience research.

This role involves conducting research to understand user behaviours, needs, and interactions with products and systems, and applying this knowledge to improve design and usability.

Key Responsibilities:

Conduct User Research: Plan and execute qualitative and quantitative research studies, including user interviews, surveys, usability testing, literature reviews and field observations. Define key information requirements based upon requirements / task analysis.
Analyse Data: Interpret research data to identify patterns, insights, and opportunities for improving user experience.
Collaborate with Design Teams: Work closely with designers, engineers, and product managers to integrate human factors principles into product development.
Create Interactions: Creation of interface concepts that conform to company interaction guidelines and take a human centred approach.
Evaluate Prototypes: Assess early-stage prototypes and provide actionable feedback to enhance usability and user satisfaction.
Document Findings: Prepare comprehensive reports and presentations to communicate research findings and recommendations to stakeholders.
Stay Updated: Keep abreast of the latest trends and advancements in human factors and ergonomics.
Skills Required:

Batchelor’s or Postgraduate Degree experience in in Human Factors, Ergonomics, User Experience, Psychology, Cognitive Science, or a related field.
Experience: Experience in human factors research or a related role.
Skills: Strong analytical skills, proficiency in research methodologies, excellent communication and presentation skills, and the ability to work collaboratively in a team environment.
Tools: Familiarity with research tools and software such as SPSS, R, NVivo, or similar.
Skills Preferred:

Work as part of an agile team developing user experiences for future JLR vehicles
Plan sprints, gather requirements, understand concept options and develop into detailed proposals.
Creation of concepts, review and refine with cross functional stakeholders and brand partners.
Build into prototyping system to allow for testing.
Work closely with user interface researchers to devise UX requirements for seamless, frictionless user journeys.
Have a strong knowledge and experience of developments in the area of human machine interfaces.
Education:

Batchelor’s or Postgraduate Degree experience in in Human Factors, Ergonomics, User Experience, Psychology, Cognitive Science, or a related field

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 Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.