At a Glance
- Tasks: Build and enhance risk models across various sectors like credit and insurance.
- Company: Join a leading firm in risk modelling with a collaborative culture.
- Benefits: Competitive salary up to £90,000, strong bonuses, and flexible remote work.
- Other info: Dynamic role with opportunities to work on diverse risk projects.
- Why this job: Make a real impact by creating innovative risk models from scratch.
- Qualifications: Strong background in risk modelling and proficiency in R, Python, or SAS.
The predicted salary is between 90000 - 90000 £ per year.
Build models across credit, insurance, pricing, and more. Leading model development from the ground up to drive business impact. A great next step for a data scientist who thrives in the modelling space.
We’re looking for a Senior Data Scientist with a passion for building risk models. If you’re the kind of data scientist who doesn’t just tweak existing models but creates them from scratch, this is your chance to make a real impact!
What you’ll be doing
This role is all about risk (we can’t stress that enough!). We’re looking for someone technically strong (likely a data scientist or similar) with a proven background in modelling risk across different environments. As part of a specialist Risk Modelling Team, you’ll operate in a collaborative, matrix-style environment. Your work will include model development, enhancement, and forecasting, ensuring outputs are accurate, robust, and clearly communicated.
This role is also a chance to work on variations of risk; you’ll model across multiple areas and projects, outside of a highly regulated environment. They need someone adaptable, curious, and genuinely passionate about risk modelling. Your projects could include insurance risk, asset risk, financial risk, pricing risk, credit risk, climate risk and more.
You’ll thrive on building and enhancing models from the ground up, bridging the gap between complex statistical techniques and clear, actionable insights for stakeholders. You’ll work closely with senior leaders, collaborate across functions, and play a key role in strategic projects. Sound like you? Apply now!
What experience you’ll need
- Strong background in risk modelling and using these insights to inform business decisions
- Proven experience building risk models from scratch and enhancing existing ones
- Excellent skills in R, Python, or SAS
- Experience leading complex model updates (both operational enhancements and full development projects) with clear communication of outcomes
- Ability to present to stakeholders and translate risk issues into business applications
- Exposure to multiple risk types (insurance, pricing, climate, asset, credit, etc.)
- Knowledge of model risk management
- Experience working outside regulated risk environments
- Desirable: Industry experience in finance, automotive, or similar sectors, plus exposure to advanced techniques like machine learning or predictive modelling
What you’ll get in return
Up to £90,000 base salary, plus a strong bonus and a comprehensive benefits package. You’ll work from the London office three days per week, with flexibility to work remotely the rest of the time.
Senior Data Scientist - Risk Modelling in London employer: Energy Jobline ZR
Join a forward-thinking company that values innovation and collaboration, where as a Senior Data Scientist in Risk Modelling, you will have the opportunity to build impactful models from scratch in a dynamic London environment. With a strong emphasis on employee growth, you will benefit from a comprehensive benefits package, flexible working arrangements, and the chance to work alongside senior leaders on strategic projects that drive real business outcomes.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist - Risk Modelling in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who work in risk modelling. A friendly chat can lead to insider info about job openings or even referrals that could give you a leg up.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your risk models and projects. This is your chance to demonstrate your ability to build models from scratch and how they’ve driven business impact. Make it easy for potential employers to see what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. You’ll need to explain complex statistical techniques in a way that makes sense to stakeholders. Practice presenting your past projects and the insights they provided to businesses.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate data scientists who thrive in the modelling space. Your next big opportunity could be just a click away, so get your application in!
We think you need these skills to ace Senior Data Scientist - Risk Modelling in London
Some tips for your application 🫡
Show Your Passion for Risk Modelling:When writing your application, make sure to highlight your genuine passion for building risk models. We want to see that you’re not just about tweaking existing models but are excited about creating them from scratch and making a real impact!
Be Clear and Concise:In your written application, clarity is key! Use straightforward language to explain your experience with risk modelling. We appreciate applicants who can communicate complex ideas in a way that’s easy to understand for stakeholders.
Tailor Your Experience:Make sure to tailor your application to reflect your experience with different types of risk, like credit or insurance. We’re looking for someone adaptable, so show us how your background aligns with the various projects we work on!
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 this exciting opportunity. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Energy Jobline ZR
✨Know Your Models Inside Out
Make sure you can discuss your experience with building risk models in detail. Be ready to explain the methodologies you used, the challenges you faced, and how you overcame them. This shows your depth of knowledge and passion for the subject.
✨Showcase Your Technical Skills
Brush up on your R, Python, or SAS skills before the interview. Be prepared to discuss specific projects where you applied these languages to develop or enhance models. If possible, bring examples of your work to demonstrate your capabilities.
✨Communicate Clearly
Since you'll be translating complex statistical techniques into actionable insights, practice explaining your work in simple terms. Think about how you would present your findings to stakeholders who may not have a technical background.
✨Be Adaptable and Curious
Demonstrate your adaptability by discussing experiences where you had to pivot or learn new techniques quickly. Show your curiosity by asking insightful questions about the company's approach to risk modelling and the types of projects you might work on.
