At a Glance
- Tasks: Lead the development of innovative financial risk models and forecasting.
- Company: Join a forward-thinking financial services team in London.
- Benefits: Enjoy a competitive salary, 20%+ bonus, and hybrid working options.
- Why this job: Make a real impact with your data science skills in a collaborative environment.
- Qualifications: Strong background in data science, model building, and statistical tools required.
- Other info: Mentor junior analysts and engage with industry experts to stay ahead.
The predicted salary is between 54000 - 126000 £ per year.
Job Description
Financial Services
- Build game-changing forecasting models.
- Take the lead in developing complex financial risk models from the ground up.
- Hybrid role in London – minimum three days in the office per week.
If you’re the kind of data scientist who doesn’t just tweak models but creates them from the ground up, this is your chance to make a real impact. We’re looking for a commercially minded Senior Risk Modeller with a strong data science background to join a forward-thinking team shaping critical financial forecasts. In this role, you’ll take ownership of sophisticated models that help make major business decisions – from residual value forecasting to insurance pricing and economic capital.
What you’ll be doing:
It’s a role for someone who thrives on building and enhancing models from scratch, who can bridge the gap between complex statistical techniques and clear, actionable insights for stakeholders. You’ll work closely with senior leaders, collaborate across functions, and have a direct hand in strategic projects, all while enjoying the flexibility of hybrid working and the rewards of a generous bonus scheme.
You’ll be part of a specialist Asset Risk Modelling Team, operating in a collaborative, matrix-style environment. Your work will include model development, enhancement, and delivering forecasting models while ensuring outputs are accurate, robust, and clearly communicated.
You’ll partner with SMEs to own outcomes, mentor junior analysts, and engage with external experts to stay ahead of best practice. From modelling the impact of electric vehicle transitions to refining customer pricing models, your influence will be felt across the business… sound like you? Apply now!
What experience you’ll need to apply:
- Solid track record in forecasting and data analysis/data science, with hands-on experience building and enhancing complex models from scratch
- Proficiency with statistical tools and programming languages such as R, Python, or SAS
- Experience leading complex model updates – both operational enhancements and full development projects – with the ability to clearly communicate outcomes to stakeholders
- Strong problem-solving skills, able to design creative and commercially strong modelling solutions
- Commercially aware, with a good understanding of market trends and the financial impact of modelling decisions
- A strong academic background (Bachelor’s or Master’s) in Statistics, Mathematics, Economics, Data Science, or a related discipline.
- Ability to manage multiple projects and stakeholders, prioritising effectively to meet deadlines
- Desirable: industry experience in sectors such as finance, automotive or similar, and exposure to advanced techniques like machine learning or predictive modelling
What you’ll get in return:
A salary of up to £90,000 plus a 20%+ bonus, alongside a comprehensive benefits package. You’ll be working in the London office, a minimum three days per week and the rest remote.
What’s next?
Apply with your updated CV, and we’ll review your application as soon as possible to arrange a conversation. For any questions, just drop Tegan an email.
Senior Risk Data Scientist employer: ADLIB Recruitment | B Corp™
Contact Detail:
ADLIB Recruitment | B Corp™ Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Risk Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in financial risk modelling. Understanding current market dynamics and how they influence forecasting models will help you stand out during discussions with our team.
✨Tip Number 2
Showcase your experience with specific statistical tools like R, Python, or SAS in your conversations. Be prepared to discuss how you've used these tools to build complex models from scratch, as this is a key requirement for the role.
✨Tip Number 3
Prepare examples of past projects where you led model updates or enhancements. Highlight your problem-solving skills and how you communicated outcomes to stakeholders, as this will demonstrate your ability to bridge technical and business needs.
✨Tip Number 4
Network with professionals in the financial services sector, especially those involved in risk modelling. Engaging with industry experts can provide insights that may be beneficial during your interview process.
We think you need these skills to ace Senior Risk Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in forecasting and data analysis. Emphasise your hands-on experience with building complex models from scratch, as this is a key requirement for the role.
Showcase Technical Skills: Clearly list your proficiency in statistical tools and programming languages such as R, Python, or SAS. Provide examples of how you've used these skills in previous roles to lead model updates or enhancements.
Highlight Problem-Solving Abilities: In your application, include specific examples of how you've designed creative modelling solutions. This will demonstrate your strong problem-solving skills and your ability to communicate outcomes effectively to stakeholders.
Include Relevant Experience: If you have industry experience in finance, automotive, or similar sectors, make sure to mention it. Also, highlight any exposure to advanced techniques like machine learning or predictive modelling, as these are desirable for the position.
How to prepare for a job interview at ADLIB Recruitment | B Corp™
✨Showcase Your Model-Building Skills
Be prepared to discuss specific examples of complex models you've built from scratch. Highlight your problem-solving approach and the impact these models had on business decisions.
✨Communicate Clearly with Stakeholders
Practice explaining technical concepts in simple terms. Since you'll be working closely with senior leaders, being able to convey your findings and recommendations clearly is crucial.
✨Demonstrate Commercial Awareness
Research current market trends and how they relate to financial modelling. Be ready to discuss how your modelling decisions can influence business outcomes and align with the company's goals.
✨Prepare for Technical Questions
Brush up on your knowledge of statistical tools and programming languages like R, Python, or SAS. Expect questions that test your understanding of forecasting techniques and model enhancements.