At a Glance
- Tasks: Transform ideas into data-driven solutions using Generative AI and machine learning.
- Company: Join Experian, a global leader in data and technology with a people-first culture.
- Benefits: Enjoy hybrid working, competitive pay, generous leave, and wellness initiatives.
- Other info: Be part of an award-winning workplace that values diversity and innovation.
- Why this job: Make a real impact in AI engineering while growing your skills in a dynamic environment.
- Qualifications: Experience in data science, machine learning, and Python programming is essential.
The predicted salary is between 55000 - 65000 € per year.
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments. We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland.
The Generative AI Centre of Expertise (GenAI CoE) at Experian helps teams across Experian's UK business. It improves products using Generative AI, machine learning, and automation. The centre has a focus on responsible, measurable impact.
This is a mid-level, hybrid role for a data scientist who enjoys hands‑on work and wants to grow into AI engineering. You'll report into the Head of Machine Learning and work across two connected areas:
- Experimentation and evaluation (data science): framing problems, designing experiments, defining success metrics, analysing results, and understanding model/system behaviour in product contexts.
- AI engineering: build GenAI systems (prototypes through to production‑ready components), supported by experienced colleagues.
A big part of the job is choosing the right approach — when GenAI is valuable, and when simpler analytics or ML is the better answer.
What you'll do:
- You will work with product, engineering, and business teams to turn fuzzy ideas into clear problem statements, assumptions, and success metrics.
- Design and run experiments to evaluate GenAI systems, including baseline comparisons, error analysis, and understanding failure modes.
- Help refine GenAI solutions, using modern development practices and AI-assisted coding tools to iterate quickly.
- Communicate results, including trade‑offs, limitations, and recommendations for what to do next.
- Share insights with the team and spend ~10% of your time on learning and knowledge sharing.
Qualifications:
- You have experience working as a data scientist (or in a similar role), applied machine learning, and Python programming.
- You are comfortable working with incomplete information, and enjoy figuring things out through exploration and experimentation.
- You are keen to develop broader skills across AI engineering and product‑focused delivery.
- You are curious, reflective, and thoughtful in your approach, comfortable challenging your own assumptions and engaging constructively with the ideas and work of others.
- You think beyond your scope: you join up product, data, and engineering context to spot issues early and improve decisions.
It would be great if you also have:
- Exposure to software engineering practices such as version control, testing, or object‑oriented programming.
- You will understand how companies deploy or run AI systems in practice through cloud services or containerised environments.
- Experience working with product managers, engineers, or other team members in a collaborative setting.
- Experience explaining technical concepts or analysis to non‑technical partners.
Additional Information:
- Benefits package includes hybrid working – 2 days in the office.
- Great compensation package and discretionary bonus plan.
- Core benefits include pension, Bupa healthcare, sharesave scheme and more!
- 25 days annual leave with 8 bank holidays and 3 volunteering days. You can also purchase additional annual leave.
Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award‑winning; World's Best Workplaces 2024 (Fortune Top 25), Great Place To Work in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.
Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
Data Scientist – GenAI & AI Engineering employer: Experian Health
Experian is an exceptional employer that prioritises employee growth and well-being, offering a hybrid working model and a comprehensive benefits package that includes generous annual leave, healthcare, and a discretionary bonus plan. With a strong focus on diversity, equity, and inclusion, Experian fosters a collaborative and innovative work culture, recognised as one of the World's Best Workplaces, making it an ideal environment for data scientists eager to develop their skills in AI engineering while contributing to meaningful projects.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist – GenAI & AI Engineering
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Experian. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a project that highlights your data science and AI engineering abilities. Bring it up during interviews to demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions related to data science and AI. Mock interviews with friends or mentors can help you nail your responses.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, you’ll find all the latest roles and updates directly from us.
We think you need these skills to ace Data Scientist – GenAI & AI Engineering
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Data Scientist role. Highlight your experience with Generative AI, machine learning, and Python programming. We want to see how your skills align with what we're looking for!
Show Your Problem-Solving Skills:In your application, share examples of how you've tackled complex problems in the past. We love candidates who can frame issues clearly and design effective experiments, so don’t hold back on showcasing your analytical prowess!
Communicate Clearly:When writing your application, keep it clear and concise. We appreciate straightforward communication, especially when it comes to explaining technical concepts. Make it easy for us to understand your thought process and insights.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, you’ll find all the details about the position there!
How to prepare for a job interview at Experian Health
✨Know Your Data Science Fundamentals
Brush up on your data science basics, especially around machine learning and Python programming. Be ready to discuss how you've applied these skills in real-world scenarios, as this role at Experian will require you to frame problems and design experiments.
✨Understand Generative AI
Familiarise yourself with Generative AI concepts and their applications. Be prepared to explain when GenAI is the right approach versus simpler analytics. This will show that you can think critically about the tools at your disposal.
✨Prepare for Collaboration Questions
Since you'll be working closely with product managers and engineers, think of examples where you've successfully collaborated in a team setting. Highlight your ability to communicate technical concepts to non-technical partners, as this is crucial for the role.
✨Show Your Curiosity and Growth Mindset
Experian values curiosity and a willingness to learn. Be ready to discuss how you've challenged your own assumptions and what steps you've taken to grow your skills in AI engineering or related areas. This will demonstrate your fit within their innovative culture.
