Senior Data Scientist/ Senior Risk Scientist

Bristol
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - Pricing & Risk ML Expert

Senior Data Scientist - Pricing & Risk Analytics

Senior Data Scientist - Energy Risk & Modeling

Senior Data Scientist – US Credit Risk ML, Remote M/W F

Senior Data Scientist: Open Banking Credit Risk & ML Production

Senior Data Scientist: Forecasting, Risk & AI (Flexible)

Senior Risk Scientist Opportunity in Bristol, UK

Location: Bristol, UK (Hybrid 2 days in the office)
Permanent role
Salary: £80,0000-£95,000 dependant on experience

About the Company:

My client is a leading player in the cyber reinsurance industry, focused on innovative solutions to manage and mitigate cyber risks. Utilising cutting-edge technology and data analytics, they develop proprietary models that drive the business forward.

The Role:
Seeking an experienced and highly skilled Senior Risk Scientist to join the dynamic team in Bristol. In this crucial role, you will be at the forefront of developing and refining proprietary cyber risk model, Cybertooth. If you have a strong background in large-scale stochastic model development, high-performance scientific computing, and expertise in statistical modelling and probability, this could be the perfect opportunity for you.

Key Responsibilities:

Contribute significantly to the development and enhancement of Cybertooth, ensuring its reliability in assessing cyber risks.
Collaborate with cross-functional teams to integrate new data sources and methodologies.
Conduct advanced statistical analyses, industry threat assessments, and reporting to support cyber risk evaluation.
Optimise the computational performance and scalability of Cybertooth simulations.
Provide technical leadership and mentorship to junior team members.
Stay informed on the latest advancements in cyber risk measurement, data science, and high-performance computing.What We're Looking For:

At least 5 years of experience in a related field, such as risk/catastrophe modelling, quantitative finance, or data science, with a focus on large-scale simulations.
Proven expertise in stochastic model development and high-performance scientific computing.
Proficiency in scientific Python; experience with Spark, CUDA, SQL, and Databricks is a plus.
Strong problem-solving abilities and the capacity to work both independently and collaboratively.
Excellent communication skills, with the ability to present complex technical information to non-technical audiences.
A degree in a STEM field or equivalent industrial experience.Why Join Us?

Competitive salary and benefits package, including a 5% pension, 28 days of holiday plus bank holidays, private medical insurance, and death-in-service benefit.
Opportunity to work with cutting-edge technology and innovative solutions in the cyber reinsurance industry.
A collaborative and inclusive work environment.
Career growth and development opportunities.This is an exciting opportunity to contribute to a forward-thinking company that is shaping the future of cyber risk management. If you're ready to take on a new challenge and make a significant impact, we'd love to hear from you

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.