Data Scientist in Redhill

Data Scientist in Redhill

Redhill Full-Time 40000 - 50000 £ / year (est.) Home office (partial)
AXA Group

At a Glance

  • Tasks: Use data to solve business challenges and build AI models for smarter decisions.
  • Company: Join AXA, a forward-thinking company that values innovation and collaboration.
  • Benefits: Flexible working arrangements, competitive salary, and opportunities for continuous learning.
  • Other info: Work smart with a balance between home and office, plus great career growth potential.
  • Why this job: Make an impact with data-driven insights and develop your skills in a dynamic environment.
  • Qualifications: Degree in a quantitative field and experience with machine learning techniques.

The predicted salary is between 40000 - 50000 £ per year.

Join us as a Data Scientist and help solve tough business challenges with data-driven solutions. Using our cloud-based data lake, you'll build advanced machine learning and AI models to improve how the organisation understands and uses data. You'll explore and question data, turning insights into opportunities and supporting smarter decisions. Working alongside your colleagues, you'll develop stories from data that are easy to understand and impactful. We encourage continuous learning through experimentation, helping you grow your skills and business understanding. You’ll deliver valuable insights, diagnose issues, and communicate findings clearly to support business success and stakeholder confidence.

Key responsibilities

  • Elicit, specify, and document requirements for straightforward subject areas, ensuring clear boundaries and managing agreed deliverables.
  • Identify, validate, and leverage simple internal and external data sets generated from non-complex processes.
  • Develop, with guidance, predictive and real-time model-based insights to add value and support decision‑making.
  • Find, acquire, clean, and integrate data to ensure it is fit for purpose, with support as needed.
  • Collaborate with stakeholders to explore data, formulate hypotheses, and use models and analytic tools to uncover insights.
  • Apply a range of basic analytical techniques, including data mining, pattern matching, forecasting, visualisation, and simple machine learning.
  • Independently develop basic machine learning models to generate insights, predict behaviours, and create value.
  • Present data insights visually and creatively to help both technical and non‑technical audiences understand findings and support decision‑making.

Work arrangements

At AXA we work smart, empowering our people to balance their time between home and the office in a way that works best for them, their team and our customers. You'll work at least two days a week (40%) away from home, moving to three days a week (60%) in the future. Away from home means attending the office, visiting clients or attending industry events. We’re also happy to consider flexible working arrangements, which you can discuss with Talent Acquisition.

Your skills & experience

  • Degree in computer science, mathematics, statistics, operations research, or a related quantitative discipline.
  • Proven experience in applying and evaluating machine learning techniques to new datasets and problems using programming languages such as Python and SQL within a regulated environment.
  • Skilled in identifying issues within machine learning systems and data and making practical recommendations for improvements.
  • Knowledge of cloud and machine learning platforms such as Azure, ML services, and Databricks, with awareness of their applications.
  • Able to produce clear reports and publish model outputs that meet customer requirements and adhere to organisational standards.
  • Capable of designing, coding, testing, documenting, and refactoring moderately simple programs or scripts, ensuring high‑quality and well‑engineered results.
  • Familiar with advanced analytical techniques including data and text mining, pattern matching, forecasting, semantic and sentiment analysis, network and cluster analysis, neural networks, and more.
  • Demonstrated ability to work effectively as part of a data science team, engaging with users to prototype, refine, and monitor progress, and to identify and resolve issues during development activities.

As a precondition of employment for this role, you must be eligible and authorised to work in the United Kingdom.

Equal opportunities statement

We’re proud to be an Equal Opportunities Employer and don’t discriminate against employees or potential employees based on protected characteristics. If you have a long‑term condition or disability and require adjustments during the application or interview process, we’re proud to offer access to the AXA Accessibility Concierge. For our support, please send an email to leanne.white@axa‑insurance.co.uk.

Data Scientist in Redhill employer: AXA Group

At AXA, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters continuous learning and collaboration. As a Data Scientist, you'll have the opportunity to work with cutting-edge technology in a flexible environment that supports your professional growth while balancing work and personal life. Our commitment to diversity and inclusion ensures that every employee feels valued and empowered to contribute meaningfully to our mission.

AXA Group

Contact Details:

AXA Group Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Scientist in Redhill

Tip Number 1

Network like a pro! Reach out to current employees at AXA or in the data science field on LinkedIn. Ask them about their experiences and any tips they might have for landing a role. Personal connections can make a huge difference!

Tip Number 2

Prepare for those interviews! Brush up on your machine learning techniques and be ready to discuss how you've applied them in real-world scenarios. Practice explaining complex concepts in simple terms, as you'll need to communicate findings clearly to both technical and non-technical audiences.

Tip Number 3

Show off your projects! If you’ve worked on any data science projects, whether personal or professional, make sure to highlight them. Create a portfolio showcasing your skills in Python, SQL, and any cloud platforms you've used. This will give you an edge over other candidates.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at AXA. Good luck!

We think you need these skills to ace Data Scientist in Redhill

Machine Learning
Data Mining
Pattern Matching
Forecasting
Data Visualisation
Python
SQL

Some tips for your application 🫡

Tailor Your CV:Make sure your CV speaks directly to the Data Scientist role. Highlight your experience with machine learning, data analysis, and any relevant programming skills like Python and SQL. We want to see how your background aligns with our needs!

Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you're the perfect fit for this role. Share specific examples of how you've tackled data challenges in the past and how you can bring value to our team. Keep it engaging and personal!

Showcase Your Projects:If you've worked on any interesting data projects, make sure to mention them! Whether it's a predictive model or a data visualisation, we love seeing how you've applied your skills in real-world scenarios. Include links if possible!

Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it’s super easy!

How to prepare for a job interview at AXA Group

Know Your Data

Before the interview, dive deep into the data-related projects you've worked on. Be ready to discuss specific datasets, the challenges you faced, and how you applied machine learning techniques. This will show your practical experience and understanding of data-driven solutions.

Master the Basics of Machine Learning

Brush up on fundamental machine learning concepts and be prepared to explain them clearly. You might be asked to describe how you would approach a problem using predictive models or how you would clean and integrate data. Make sure you can articulate your thought process!

Visualisation is Key

Since you'll need to present data insights to both technical and non-technical audiences, practice how you would visually communicate your findings. Bring examples of your work that showcase your ability to create impactful visualisations that tell a story.

Engage with Stakeholders

Be ready to discuss how you've collaborated with stakeholders in the past. Think of examples where you explored data together, formulated hypotheses, and how your insights influenced decision-making. This demonstrates your teamwork skills and your ability to translate data into actionable insights.