At a Glance
- Tasks: Develop and deploy machine learning models to impact millions of customers.
- Company: Join a leading insurance firm with a focus on innovation and collaboration.
- Benefits: Generous pension, annual bonuses, share schemes, and 30 days' holiday.
- Other info: Dynamic teams, excellent career growth, and a supportive work environment.
- Why this job: Make a real difference in people's lives through data-driven solutions.
- Qualifications: Experience in AI/ML, strong Python and SQL skills, and a passion for data science.
The predicted salary is between 50000 - 70000 £ per year.
About this opportunity: You will be working in multidisciplinary teams and support all stages of a project - from exploring the problem statement and experimenting with different modelling approaches to developing industrialised applications powered by Machine Learning.
As a data scientist you'll:
- Develop experimental models and machine learning applications in Python alongside our Data Engineers (who build the data pipelines and ensure quality).
- Deliver production Machine Learning models across the full reach of the Insurance Pensions & investments business - from predicting Pension balances to identifying which of our customers may fall into financial difficulty and need a helping hand.
- Collaborate in multidisciplinary squads, regularly communicating key findings to our business partners.
Your models will have a material impact on the lives of up to 30m+ customers across the whole of the UK!
What you'll need:
- Previous experience of deploying AI and ML models within a similar sized organisation.
- Strong theoretical and applied knowledge of Statistical Modelling and/or Machine Learning techniques is required such as: regression, clustering, attribution (econometrics / MMM), decision trees and gradient boosting machines (random forest, XGBoost, LGBM) and significance testing.
- A good understanding of Python and SQL is also required including how to write modular Pythonic code, familiarity with the core Python data structures and fluency with pandas; a familiarity with unit testing would be beneficial.
- The ability to present the takeaways from these techniques in a clear, visual manner to support senior business partner's decision making is key to the success of our projects.
- Experience implementing and supporting Machine Learning systems including automating data validation, model training, model validation and model monitoring would also be very useful.
We're particularly keen to hear from individuals who have a track record of delivering data science projects within commercial environments. For example, those with experience of having successfully industrialised and delivered data science solutions for large scale industry applications.
We also offer a wide-ranging benefits package, which includes:
- A generous pension contribution of up to 15%.
- An annual bonus award, subject to Group performance.
- Share schemes including free shares.
- Benefits you can adapt to your lifestyle, such as discounted shopping.
- 30 days' holiday, with bank holidays on top.
- A range of wellbeing initiatives and generous parental leave policies.
Data Scientist employer: Lloyds Banking Group
Join a forward-thinking company that values innovation and collaboration, where as a Data Scientist, you will play a pivotal role in shaping the future of financial services for over 30 million customers across the UK. With a strong emphasis on employee growth, we offer extensive training opportunities, a generous benefits package including a 15% pension contribution and 30 days of holiday, and a vibrant work culture that encourages creativity and teamwork. Experience the unique advantage of working in multidisciplinary teams, where your contributions directly impact real-world outcomes while enjoying a supportive environment that prioritises your well-being.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and Python. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and practising common data science questions. Be ready to discuss your past projects and how you've applied statistical modelling techniques in real-world scenarios.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from passionate candidates. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience with AI and ML models, and don’t forget to mention your Python and SQL skills. We want to see how your background aligns with what we’re looking for!
Showcase Your Projects:Include specific examples of data science projects you've worked on, especially those that had a real impact. We love seeing how you’ve applied statistical modelling and machine learning techniques in practical scenarios.
Keep It Clear and Concise:When writing your application, be clear and concise. Use straightforward language to explain your experience and skills. Remember, we want to understand your journey without getting lost in jargon!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen to join the StudySmarter team!
How to prepare for a job interview at Lloyds Banking Group
✨Know Your Models Inside Out
Make sure you can discuss the machine learning models you've worked with in detail. Be ready to explain how you’ve applied techniques like regression, clustering, and decision trees in your previous projects. This shows you not only understand the theory but can also apply it practically.
✨Show Off Your Python Skills
Brush up on your Python and SQL skills before the interview. Be prepared to demonstrate your ability to write clean, modular code and use libraries like pandas effectively. You might even be asked to solve a coding challenge, so practice writing code that’s both efficient and easy to read.
✨Communicate Clearly
Since you'll need to present findings to business partners, practice explaining complex concepts in simple terms. Use visuals if possible, as this can help convey your points more effectively. Think about how you would summarise your work for someone without a technical background.
✨Prepare Real-World Examples
Have a few examples ready that showcase your experience in deploying AI and ML models in commercial settings. Discuss the challenges you faced, how you overcame them, and the impact your work had on the business. This will demonstrate your ability to deliver results in a real-world context.
