Senior Data Scientist

Hastings Direct
Melton Mowbray
3 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Job title: Senior Data Scientist


Location: London / Leicester / Bexhill


Welcome to Hastings Direct


We’re a digital insurance provider with a clear strategy to become the best and biggest player in the UK market. As a company, we’ve made huge investments in our technology, pricing, data and analytics capabilities over the past few years, along with nurturing our 4Cs culture and substantial investment in our people. And as a Finance team, we're doing exactly the same – building a market leading finance technology platform, investing in our team and our approach to leadership development, with a real focus on commercially adding value to the business.


The fact you’re now reading this job advert means we’ve tempted you to find out more about #lifeatHD. If you like what you see, we hope you'll consider joining our team.


We have high standards and understand some people may not apply for jobs unless they feel they tick every box. If you’re excited about joining us and think you have some of what we are looking for, even if you’re not 100% sure, we would love to hear from you.


Role overview

The Senior Data Scientist will oversee projects and modelling exercises which deliver cutting‑edge data assets and predictive models that feed into Hastings’ market‑leading pricing activities. This role is within a combined team of Actuaries and Data Scientists, championing the adoption of the latest machine learning (ML) techniques to leverage powerful insights from vast amounts of customer information beyond what traditional modelling techniques can provide.


The Senior Data Scientist will use their understanding of Data Science techniques to solve insurance problems and to deliver claims cost models. Established traditional techniques, but we are looking to leverage advanced ML techniques to maximise commercial value, while ensuring a fair outcome for customers. The DS Manager would manage a small team, who would assist the creation of models and would require mentoring and support in their development.


The role would suit a Data Scientist with a track record of delivering General Insurance pricing models, or a newly/nearly qualified Actuary with experience and a keen interest in Data Science.


Key Responsibilities

  • Taking the technical lead in projects that create and maintain analytical tools to support our technical models and serve as the foundation for our premium.
  • Develop best‑in‑class models to predict claims outcomes, fraud and other KPIs.
  • Engineer powerful new rating factors to be deployed into our rating algorithms and understand their impact and value.
  • Identify, analyse and monetise new data sources.
  • Manage and mentor more junior members of the Technical Pricing team.
  • Ensure robustness of models across both traditional and non‑traditional model types.

Essential skills/experience

  • Experience undertaking predictive modelling – including the use of GBMs – in a General Insurance pricing environment.
  • Experience in the creation and development of models in Python, using the main Data Science libraries.
  • Keen interest in emerging ML techniques and the opportunities that these present for insurance companies.
  • Experience in the delivery of large model reviews – from initial modelling to implementation.
  • Strong Structured Query Language (SQL) coding skills and ability to manipulate data.
  • Stakeholder management and communication skills with the ability to present technical ideas to a non‑technical audience.

Desirable

  • Experience in a Personal Lines pricing team (motor or home).
  • Experience with using GitHub for version control and as a code collaboration tool.
  • Eagerness to work cross‑functionally with Data Engineers, Data Scientists, Actuaries and Risk Pricing Analysts.
  • Experience of the application of non‑traditional techniques to pricing.

The interview process

Our interview process involves the following stages:



  • Recruiter screening call
  • 1st stage interview – initial intro with hiring leader
  • 2nd interview (technical) will include a panel
  • 3rd call with hiring leader

As a Disability Confident employer, we’re committed to ensuring our recruitment processes are fully inclusive – what this means to you is if you’re applying for a job with us, you’ll have fair access to support and adjustments throughout your recruitment journey. We also welcome applications through the Disability Confident Scheme (DCS). For more information on the DCS, please visit our inclusive business page on our careers website.


Benefits

In addition to a competitive salary and £5k car allowance you will also receive…


Flexible working – we champion a flexible hybrid working approach – please speak to your recruiter to discuss in more detail.


Competitive bonus scheme – all colleagues are eligible for our annual 4Cs performance bonus.


Physical wellbeing – as a Band 4 colleague, Hastings pays for you to receive private medical insurance (PMI). This gives you flexibility and convenience to see a specialist or consultant and allows you to decide when and where you will be seen.


Financial wellbeing – we provide 4× your salary with our life assurance cover, income protection at no extra cost, and matched pension contributions up to 10%. We also offer discounts, cashback, free independent mortgage advice and free access to financial wellbeing support.


Mental wellbeing programme – we have the Thrive mental health app, our colleague assistance programme available 24/7, our own in‑house mental health first aiders, support groups and a dedicated team to make sure we are covering your needs.


There’s more! – 27 days annual leave + bank holidays, with the option to buy or sell one of your weeks, access to our health‑care cashback plans, dental plans, discounted health assessments, Cycle to Work and tech schemes, discounted and free onsite facilities, social events throughout the year and much more….


Join us and you’ll find a different way of doing things. We call it the 4Cs. We focus on getting it right for our colleagues, customers, company and community. As one of our colleagues, you’ll be helping to drive our growth, so in return, we’ll give you all the support, training and development you need. Our 4Cs principles are simple: we believe by creating the right culture for our colleagues and giving them the right tools to do their job, we’ll deliver good outcomes for every customer, helping us to grow the company profitably and sustainably and allowing us to invest in the communities we serve.


Hastings Group is an equal opportunities employer which means we treat people fairly. We welcome applications from all suitably skilled persons regardless of their gender, age, race, disability, ethnic background, religion/belief, sexual orientation, gender reassignment or marital/family status. Please also note that we have a thorough referencing process, which includes credit and criminal record checks.


At Hastings Direct, we’re committed to creating an inclusive environment where everyone has the opportunity to succeed. If you require any reasonable adjustments during the recruitment process, we encourage you to be open with us. Our recruitment team is here to provide the support you need to ensure a fair and accessible experience for all.


#J-18808-Ljbffr

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.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.