Data Scientist

Peterborough
5 days ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist - London

Data Scientist | London | AI-Powered SaaS Company

Data Scientist/Machine Learning Engineer - RNA Design

Company: BGLi (part of the Markerstudy Group)

Job title: Data Scientist (mid-senior)

Location: Peterborough (hybrid working)

Role overview

The role of a data scientist in the pricing science team is a mixture of exploration and support. The Data scientists or Pricing Science are the chief avenue of new techniques, approaches, and ways of doing things into our price modelling process. They are also responsible for the maintenance of the tools that are used by the price modelling teams. As a wider level the pricing science team are expected to contribute, along with other data scientists and engineers, to the development of our tech infrastructure. There will also be occasions where a data scientist collaborates with third party partners to develop new products outside of pricing such as risk or customer behaviour scores.

Key Accountabilities & Responsibilities

Develop a strong understanding of how we price Motor and Home insurance products

Develop an understanding of how and where we can improve current processes & practice

Introduce and lead research and development projects to improve the performance and efficiency of the machine learning models  ?

Collaborate with Technical Pricing Team to identify business problems and recommend solutions?

Adapt working with our current tools and developments that are mainly based on R and Python?

Collaborate with our data scientists in the maintenance of the existing tools and platforms 

Work with other data scientists

Skills, Experience and Knowledge

Programing skills in Python or R (or both) and their relevant data science and statistics libraries?

Knowledge on data manipulations, machine learning, advanced analytics, and statistical techniques ?

Ability in communicating with the team members and written and verbal presentation skills ?

Ability to engage in teamwork and to collaborate with the team to produce the best outputs

Degree qualification in relevant discipline e.g., mathematics, computer science, computer engineering, statistics? (advantageous)

Experience in insurance or other financial services (advantageous)

Why us?

Markerstudy Insurance Services Limited (MISL) is one of the largest Managing General Agents in the UK. With a strong presence in the UK motor insurance market, we specialise in niche motor cover, where our solid market knowledge and experience enables us to create highly targeted products.

Our success is underpinned by our underwriting strategy to identify and apply special risk factors to the customers’ advantage. That, and our skilled underwriting technicians who are friendly, accessible and empowered to make decisions.

We only transact business through professional UK insurance intermediaries and we take pride in fostering excellent working relationships. Our products feature prominently on Aggregators' sites, such as (url removed), Go Compare and Compare the Market, via our broker partners.

What we offer in return?

A collaborative environment

Hybrid/Flexible working model

25 days annual leave plus of Bank Holidays and the ability to buy an additional three days holiday

Health Cash Plan

A benefit scheme that offers discounts and cashback on shopping, restaurants, travel and more

Life Assurance 4x annual salary

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.