Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Science Manager

Arch Capital Group
London
5 months ago
Applications closed

Related Jobs

View all jobs

Data Science Manager - Simulation and Digital Twins

Data Science Manager

Data Science Manager (Applied AI)

Data Science Manager

Data Science Manager - Recommendation Systems (Retail and Luxury)

Contract Data Science Manager

With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential. Our work is the catalyst that helps others achieve their goals. In short, We Enable Possibility℠.

Key Tasks & Responsibilities

Work closely with business partners to understand the business problems they are trying to solve and help develop and prioritize the best-suited analytics solutions. Collaborate in cross-functional teams and share ideas to solve complex business problems. Build strong partnerships with peers across the organization to support project goals and boarder team needs. Oversee the build of predictive models using advanced analytics techniques including GLMs, natural language processing, and machine learning. Develop powerful insights using a variety of analytical tools, techniques, and technologies, and deliver results which drive business decisions. Discover, explore, and analyse internal and external datasets for the purpose of developing advanced analytics models. Help establish best practices and repeatable processes for the Strategic Analytics team. Provide thought leadership on new, innovative techniques, approaches and software. Guide, support, mentor and develop the growing team of predictive modelers and data scientists.

Desired Skills

Ability to design, build and implement statistical models, with an understanding of a range of analytical techniques such as predictive modelling, NLP and data mining. Data manipulation and analytical skills in languages such as Python, R and / or SQL. Familiarity with cloud-based platforms such as Databricks, Snowflake and Azure is an advantage, but not essential. Effective task / project management and general organization skills. Excellent verbal and written communications skills; ability to convey complex concepts to technical and non-technical people across the organization. Exceptional teamwork skills required to play a key role in cross-functional teams. Ability to collaborate and build trusting relationships with business partners. Natural curiosity to understand the world around you and question as needed. Comfortable handling ambiguous concepts and breaking down complex problems into manageable pieces. Ability to apply critical thinking and creative problem-solving skills.

Experience

Experience in advanced analytics roles, a significant portion of which should be in the insurance industry. Experience working in an analytical role within an insurance environment is an advantage. Hands-on experience developing and deploying real-time predictive models. Experience delivering business value from small or non-standard data sets.

Qualifications

Degree in Computer Science, Engineering, Statistics, Mathematics, Actuarial Science, Data Analytics, or equivalent

14101 Arch Europe Insurance Services Ltd

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.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.