Senior Data Scientist

1st Central
Manchester
4 days ago
Create job alert

Senior Data Scientist 1st Central•Manchester, England, UK


We are 1st Central, a market‑leading insurance company utilising smart data and technology at pace. Rapid growth has been based on giving our 1.4 million customers exactly what they want: great value insurance with an excellent service. And that’s the same for our colleagues too; we won Insurance Employer of the Year at the British Insurance Awards 2024 and our Glassdoor score is pretty mega too!


We’re looking for a Senior Data Scientist to join a team of data scientists and specialists focused on delivering a portfolio of innovative services that uncover and create value from the company’s extensive information assets.


In this role you’ll work both independently and collaboratively to apply data science techniques that drive meaningful outcomes. You’ll work with large and diverse datasets from multiple sources spanning both structured and unstructured formats. Using strong critical‑thinking and problem‑solving skills you’ll analyse and interpret data, build predictive models and develop machine learning algorithms that generate actionable insights.


You’ll propose solutions to business challenges and collaborate with other teams to implement them. Recognising the dependencies Group companies have on in‑house technology the Senior Data Scientist will work closely and seamlessly with the Group’s in‑house technology provider along with data presentation/delivery teams based across multiple locations.


This is a flexible hybrid role with occasional visits to our offices in Salford Quays (Manchester) or Haywards Heath (West Sussex) when required. For those based further afield we also welcome applications from remote UK‑based workers. We offer excellent flexibility in working patterns and a company‑wide culture you can be proud to be part of.


Core Skills

  • Analytical & Technical Expertise: Proven analytical and statistical modelling skills
  • Technical Skills: Experience using Python
  • Machine Learning: Ability to build and train machine learning models
  • Professional Experience: Current Data Science experience with Insurance industry exposure being advantageous but not essential
  • Organisation & Time Management: Strong time‑management and organisational abilities
  • Education: Degree in Data Science or another quantitative field

What’s Involved

  • You’ll scope out and develop data services including deep learning predictive analytics and machine learning that help to solve business problems
  • You’ll perform data analysis and data collection processes that effectively support these services
  • You’ll continuously develop data sources through testing of external data
  • You’ll work individually and with team members, other teams and suppliers to deliver data science solutions. Review output of junior team members
  • You’ll help to identify opportunities across the organisation where data science can add value
  • You’ll adhere to good coding practices, work within existing risk controls, identify and report potential risks
  • You’ll comply with the requirements and act in accordance with the Group Code of Conduct and Fitness and Propriety policies at all times
  • You’ll ensure compliance with Company Policies, Values and guidelines and other relevant standards/regulations at all times

Experience & Knowledge

  • Proven experience in data science and data analysis
  • Good understanding of statistical techniques and their application including GLMs, decision trees, random forest, boosting, natural language processing, distributions, clustering, simulation and scenario analysis
  • Knowledge of data platforms and data processing including batch and real‑time automation
  • Knowledge of data structures and schemas, data preparation and cleansing
  • Experience of machine learning techniques and libraries
  • Knowledge of data science toolkits and languages such as R, Python, Scala
  • Experience of data exploration and visualisation tools
  • Good knowledge of data query languages such as SQL, HiveQL, scripting
  • Knowledge of data integration services and ETL
  • Analytical and problem‑solving aptitude
  • Understanding of a service‑based approach to professional services
  • Experience delivering through Agile change framework

Skills & Qualifications

  • Good communication skills both verbal and written
  • Good time management and organisation skills
  • Proven analytical and statistical modelling skills
  • Degree in Data Science or other quantitative field

Behaviours

  • Self‑motivated and enthusiastic with the desire to meet or exceed targets
  • Determined and passionate particularly regarding data and technology
  • A decision maker with an ability to work on own initiative or as part of a team
  • A flexible approach and positive attitude
  • Strives to drive business improvements contributing to the success of the business
  • An organised and proactive approach

What We Offer

People first. Always. We’re passionate about our colleagues and know the best people deserve an extraordinary working environment. We owe it to them so that’s what we offer. Our workplaces are energetic, inspirational and supportive. To get a taste of the advantages you’ll enjoy take a look at all our perks in full here.


Intrigued? Our Talent team can tell you everything you need to know about what we want and what we’re offering so feel free to get in touch.


Required Experience: Senior IC


Employment Type : Full‑Time


Vacancy: 1


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist - National Security (TIRE) based in Cheltenham/Hybrid

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.