At a Glance
- Tasks: Design and improve data solutions to enhance operational performance and decision-making.
- Company: Join a leading financial services company focused on innovation and customer satisfaction.
- Benefits: Generous holidays, pension contributions, employee discounts, and flexible work-life balance.
- Why this job: Make a real impact with advanced analytics and machine learning in a dynamic environment.
- Qualifications: Experience in data analysis, automation, and machine learning; strong communication skills.
- Other info: Inclusive workplace committed to diversity and personal growth.
The predicted salary is between 36000 - 60000 £ per year.
Locations Available: Bristol, London, Leeds
DLG is evolving. Across every facet of our business, our teams are embracing new opportunities and putting customers at the heart of everything they do. By joining them, you’ll have the opportunity to not just be recognised for your skills but encouraged to build upon them and empowered to do your absolute best.
What you'll be Doing
The Operational MI Analyst is responsible for designing, building, and continuously improving MI and data solutions that support operational performance. The role focuses on automating data flows, strengthening data architecture and governance, and applying advanced analytics techniques, for example machine learning, to deliver forecasting and insight that drive effective decision-making across the operational area.
Key Accountabilities
- Build, enhance, and automate operational MI dashboards, reports, and data products to provide timely, accurate, and actionable insight.
- Develop robust data pipelines and models that reduce manual effort and improve data quality, consistency, and reliability.
- Partner with a range of other business areas, including product/platform, trading and technology teams to ensure data architecture is fit for purpose and end to end customer outcomes are visible and analysed.
- Implement appropriate data governance, controls, and documentation to ensure accuracy, traceability, and compliance.
- Design, build, and deploy predictive and forecasting models using AI and machine learning techniques to support capacity planning, demand forecasting, and operational decision-making.
- Translate complex data and analytical outputs into clear insights and recommendations for operational leaders.
- Continuously identify opportunities to improve MI, analytics capability, and the use of data across the operational function.
Our hybrid model offers a 'best of both worlds' approach. When you'll be in the office depends on your role and team, but colleagues spend at least 50% of their time in the office.
What You’ll Need
- Proven experience in building and automating MI and data solutions within a financial services operational environment.
- Advanced data analysis and modelling skills (e.g. SQL, Python, R, or similar).
- Experience designing and deploying machine learning or AI models, particularly for forecasting or predictive analytics.
- Strong understanding of data architecture, data governance, and control frameworks.
- Experience working with BI and visualisation tools (e.g. Power BI, Tableau).
- Ability to work cross-functionally and communicate effectively with both technical and non-technical stakeholders.
- Experience in Commercial Insurance is preferred but not essential.
Benefits
We recognise we wouldn't be where we are today without our colleagues, that's why we offer excellent benefits designed to suit your lifestyle:
- 9% employer contributed pension
- 50% off home, motor and pet insurance, plus free Green Flag breakdown cover
- Additional optional Health and Dental insurance
- EV car scheme allows all colleagues to lease a brand new electric or plug-in hybrid car in a tax efficient way.
- Generous holidays
- Buy as you earn share scheme
- Employee discounts and cashback
- Plus, many more
We want everyone to get the most out of their time at DLG. Which is why we've looked beyond the financial rewards and created an offer that takes your whole life into account. Supporting our people to work at their best – whatever that looks like — and offering real choice, flexibility, and a greater work-life balance that means our people have time to focus on the things that matter most to them. Our benefits are about more than just the money you earn. They're about recognising who you are and the life you live.
Be yourself
Direct Line Group is an equal opportunity employer, and we think diversity of background and thinking is a big strength in our people. We're delighted to feature as one of the UK's Top 50 Inclusive Employers and are committed to making our business an inclusive place to work, where everyone can be themselves and succeed in their careers. We know you're more than a CV, and the things that make you, you, are what bring potential to our business. We recognise and embrace people that work in different ways so if you need any adjustments to our recruitment process, please speak to the recruitment team who will be happy to support you.
We are an equal opportunity employer.
Operational MI Analyst employer: Direct Line Group Careers
Contact Detail:
Direct Line Group Careers Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Operational MI Analyst
✨Tip Number 1
Network like a pro! Reach out to current employees at DLG on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Prepare for the interview by brushing up on your data skills. Be ready to discuss how you've built and automated MI solutions in the past. Show us your passion for data and analytics!
✨Tip Number 3
Don’t forget to showcase your soft skills! Being able to communicate complex data insights clearly is key. Practice explaining your past projects to someone who isn’t in the field.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at DLG.
We think you need these skills to ace Operational MI Analyst
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with MI and data solutions. We want to see how your skills align with the role, so don’t hold back on showcasing your achievements!
Show Off Your Technical Skills: Since this role involves advanced data analysis and machine learning, be sure to mention your proficiency in tools like SQL, Python, or R. We love seeing candidates who can demonstrate their technical prowess!
Communicate Clearly: Remember, you’ll be working with both technical and non-technical teams. Use clear language in your application to show us you can translate complex data insights into actionable recommendations. It’s all about making those connections!
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, it’s super easy to do!
How to prepare for a job interview at Direct Line Group Careers
✨Know Your Data Tools
Make sure you brush up on your skills with SQL, Python, or R. Be ready to discuss how you've used these tools in past roles to build and automate MI solutions. Having specific examples will show that you can hit the ground running.
✨Showcase Your Analytical Mindset
Prepare to talk about your experience with machine learning and predictive analytics. Think of a project where you applied these techniques and be ready to explain the impact it had on decision-making. This will demonstrate your ability to translate complex data into actionable insights.
✨Understand Data Governance
Familiarise yourself with data governance principles and frameworks. Be prepared to discuss how you've implemented controls and documentation in previous roles to ensure data accuracy and compliance. This shows you understand the importance of data integrity in operational performance.
✨Communicate Effectively
Practice explaining technical concepts in simple terms. You’ll likely need to communicate with both technical and non-technical stakeholders, so being able to bridge that gap is crucial. Think of examples where you successfully collaborated across teams to achieve a common goal.