junior data scientist

MarketCast

<div>
 
 Junior Data Scientist - Product
 
 
 
 
 London, UK, Reading, UK
 
 
 
 
 Role Impact
 
 
 
 As our Junior Data Scientist - Product, you'll be a pivotal player on our Data Science Product Team, which currently comprises about 15 data scientists with varying levels of seniority.
 
 
 The Junior Data Scientist - Product plays a foundational role in supporting the design, engineering, execution, and delivery of advanced data science projects and market research products at Marketcast. Operating at the intersection of quantitative market research, software engineering, and artificial intelligence, this position focuses on building the backend systems and data pipelines that clean, process, and analyse complex datasets to extract actionable consumer insights. On a daily basis, the Junior Data
 
 
 Scientist assists in writing production-quality code, developing and maintaining data pipelines, implementing machine learning models, and translating analytics into robust, reusable product features under senior guidance. By ensuring high data quality, engineering rigour, and contributing to innovative product features, this individual directly enhances the reliability and scalability of the organisation's media and entertainment analytics.
 
 
 
 We're Looking For
 
 
 
 <ul>
 <li>
 Data Engineering and Pipeline Development &ndash; Design, build, and maintain reliable data pipelines that clean, preprocess, and structure complex quantitative datasets using Python, SQL, pandas, and modern data tooling. This technical processing is performed systematically and reproducibly, with an emphasis on well- structured, version-controlled, and testable code to prepare raw survey and consumer data for downstream statistical models. Ensuring clean inputs and resilient pipelines directly prevents model drift and maintains the reliability of product outputs. Success in this responsibility is defined by the timely delivery of error-free, analytical-ready, and maintainable data pipelines to senior data scientists.
 </li>
 <li>
 Quantitative Analysis &amp; Modelling - Assist in executing statistical analyses, regression modelling, and audience segmentation under the guidance of senior team members, with a strong emphasis on mathematical rigour and a sound understanding of the methods being applied rather than their black-box use.
 </li>
 <li>
 Backend &amp; Software Development - Contribute to the backend services, APIs, and codebases that power our data products, writing clean, tested, and well-documented code under senior guidance. The analyst works within standard software engineering practices - version control, code review, automated testing, and CI/CD - to ship features that are reliable and maintainable rather than one-off scripts. This software-first approach ensures our analytical work translates into durable product infrastructure. Success is measured by code quality, adherence to engineering standards, and the stability of contributions in production.
 </li>
 <li>
 Infrastructure &amp; Deployment - Support the deployment, monitoring, and scaling of data science workloads across our cloud and infrastructure stack (e.g. containers, orchestration, and managed cloud services) under supervision. The analyst helps operationalise models and pipelines so they run reliably and cost-effectively at scale, contributing to the team's MLOps and engineering practices. This focus on robust infrastructure reduces manual intervention and improves the reliability of our products. Performance is evaluated on the stability, reproducibility, and efficiency of deployed workloads.
 </li>
 <li>
 AI &amp; LLM Integration - Support the integration of artificial intelligence APIs, large language models (LLMs), and natural language processing pipelines into existing data products. Under supervision, the analyst helps configure frameworks to streamline analytical workflows, saving dozens of hours of manual coding on client projects. Performance is evaluated on the efficiency, robustness, and classification accuracy of the automated NLP routines.
 </li>
 <li>
 Data Quality &amp; Validation - Execute rigorous quality control protocols across all assigned data products and research databases, including automated tests and validation checks wherever possible. The Junior Data Scientists systematically validate schemas, sample distributions, and statistical weights to verify data integrity, treating data validation as an engineering discipline. This preventative auditing mitigates the risk of reporting flawed conclusions to high-profile entertainment clients. Successful execution is measured by the complete absence of formatting or calculation errors in final delivery files.
 </li>
 <li>
 Client Collaboration &amp; Technical Delivery &ndash; Work closely with product managers, engineers, and senior data scientists in a collaborative, software-development style &ndash; gather requirements, contributing to technical scoping, and participating in agile ceremonies and code reviews.
 </li>
 <li>
 Cross-Functional Initiative Support - Participate actively in company-wide product development initiatives, research-on-research experiments, and technical thought leadership groups. The Junior Data Scientist collaborates across data operations, cloud engineering, product, and engineering departments to support the trial of new analytical and engineering methodologies. This cross-pollination of ideas ensures the product data science team remains at the forefront of marketing science and technical innovations. Engagement in these initiatives is demonstrated by active participation in internal sharing sessions and support for pilot projects.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 We genuinely don&rsquo;t mind what is written on your certificate. While we would love you to have a formal qualification in any discipline that builds strong analytical and problem-solving skills, we primarily care that you're clever, rigorous, and can do the job. Equivalent practical experience - whether self-taught, through bootcamps, open-source contributions, a strong portfolio, or prior industry work - is just as welcome as a formal degree.
 </li>
 <li>
 A successful applicant must demonstrate solid programming ability (Python and ideally SQL) and an interest in writing good, maintainable software - not just scripts.
 </li>
 <li>
 A successful applicant must further demonstrate a genuine appetite for technical depth, mathematical rigour, and continuous learning.
 
 
 </li>
 </ul>
 
 Who We Are
 
 
 
 MarketCast measures what moves people. Powered by AI, trained on decades of verified consumer response data, and backed by proprietary technology, MarketCast is the marketing effectiveness partner for the world's most ambitious brands, connecting emotional resonance to real-world business outcomes across advertising, sponsorships, content, brand health, and advanced analytics. With category-deep expertise spanning sports, entertainment, travel, automotive, and consumer brands, our team of
 
 
 seasoned industry strategists brings unmatched human intelligence to every engagement, turning complex data into decisive action so brands know exactly what's working, why it's working, and what to do next.
 
 
 At MarketCast, we don't just accept difference - we embrace it, support it, and thrive on it for the benefit of our global culture and success. MarketCast is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know. Check us out on LinkedIn and at: www.marketcast.com
 
 
 
 Our Values
 
 
 
 
 Move The Needle
 
 
 
 We turn insight into action and action into impact, acting with urgency and intention at every level, anticipating what's needed, executing with discipline, and driving outcomes that are measured and meaningful.
 
 
 
 Client Success is Our Scoreboard
 
 
 
 We win when our clients win. Delivering scaled, tech-enabled solutions that drive measurable impact and value to build lasting partnerships.
 
 
 
 Grow Every Day
 
 
 
 Expertise is earned continuously by investing in our craft, our colleagues, and our company.
 
 
 
 Own It
 
 
 
 Take responsibility for outcomes, not just outputs.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 Free movie tickets!
 </li>
 <li>
 29 days annual leave PLUS Bank Holidays
 </li>
 <li>
 Flextime with core hours between 10am and 3pm
 </li>
 <li>
 2 days&rsquo; work from home per week
 </li>
 <li>
 4% match pension scheme
 </li>
 <li>
 Enhanced maternity pay
 </li>
 <li>
 Regular social events in both UK locations
 </li>
 <li>
 Professional growth and career development including LinkedIn Learning
 
 
 </li>
 </ul>
 In addition to your salary, MarketCast believes in providing a competitive total rewards package for its employees. All benefits are subject to eligibility requirements, and the terms of our official plan may be modified or amended from time to time.
 
 
 GENERAL DATA PROTECTION REGULATION (UK GDPR) NOTICE: The organisation collects and processes personal data relating to its applicants, employees and former employees to manage pre-employment and employment relationships and post-employment obligations. The organisation is committed to being transparent about how it collects and uses that data and to meeting its data protection obligations. For further information on the information we collect, how it&rsquo;s used, and how it's protected, please contact the MarketCast UK HR Team.
</div>

Junior Data Scientist I

<div>
 
 Your role
 
 
 
 Are you passionate about AI/ML, programming, and automation? Do you have technical expertise in design, software development, and modeling? Do you aspire to develop the next generation of AI business applications?
 
 
 As a Data Scientist, you will collaborate with our data science and business teams to build state-of-the-art models, and perform exploratory analysis on new and existing data to identify, investigate, and solve challenges. You should be comfortable applying a variety of techniques to find the best results and capable of researching new methods to trial. You will work closely within a small team where collaboration is key to achieving our common goals.
 
 
 <ul>
 <li>
 Collaborate with the business to assess opportunities for AI/data analytics technologies and maximize their value/impact for our clients.
 </li>
 <li>
 Support the design of AI/data analytics solution architecture and work with stakeholders to develop implementation roadmaps.
 </li>
 <li>
 Support AI/data analytics solution implementation and deployment.
 </li>
 <li>
 Develop, maintain, and deploy LLM, machine learning, and natural language processing pipelines and models with high performance, quality, and stability.
 </li>
 <li>
 Partner with the business to integrate AI and machine learning solutions across various strategic platforms. Models may span across a variety of domains, including but not limited to: LLM-based agentic AI architectures, natural language processing (e.g., document classification, named entity recognition, topic modeling, advanced and semantic information search, extraction), data analytics (predictive modeling, time-series analytics, pattern recognition, recommendation engines), computer vision (OCR), and voice recognition (speech-to-text).
 </li>
 <li>
 Research and build POCs for new and innovative AI solutions and technologies.
 
 
 </li>
 </ul>
 
 Job Type
 
 
 
 Full Time
 
 
 
 Job Reference #
 
 
 
 336118BR
 
 
 
 City
 
 
 
 London
 
 
 
 Your team
 
 
 
 You&rsquo;ll be working in the IB AI Center of Excellence team in London, focusing on building AI products across the Investment Bank. The AI solutions we build support our colleagues in working more efficiently, reducing the risks we face as a bank, and generating more revenues. Moreover, our products ensure that our clients receive timely and personalized content. As a Data Scientist, you&rsquo;ll play an important role in shaping the AI landscape within the IB.
 
 
 Diversity helps us grow together. That&rsquo;s why we are committed to fostering and advancing diversity, equity, and inclusion. It strengthens our business and brings value to our clients.
 
 
 
 Your expertise
 
 
 
 <ul>
 <li>
 Master's degree or higher in a quantitative / scientific field or equivalent work experience
 </li>
 <li>
 Experience in designing and developing enterprise-scale AI and NLP solutions in the areas of Named Entity Recognition, Document Classification, Document Summarization, Topic Modeling, Sentiment Analysis, and OCR text processing.
 </li>
 <li>
 Experience building ML &amp; NLP solutions using common ML libraries and frameworks, including Pandas, Sklearn, TensorFlow, SparkML, Pytorch, etc.
 </li>
 <li>
 Skilled in end-to-end development of ML/NLP models (supervised &amp; unsupervised), including data cleaning, pipeline creation for structured/unstructured data, feature engineering, model selection/ensembles, evaluation metrics, visualization, and advanced statistical modeling (regression, spatial, time series).
 </li>
 <li>
 Ideally 2+ years of programming experience in one or more of the following: Python, R, Scala, C/C++, Matlab, SQL/Postgres, etc. Knowledge of CI/CD pipelines, Git, and GitHub/GitLab.
 </li>
 <li>
 Familiarity with Agentic AI frameworks such as LangGraph, AutoGen, etc is a plus
 </li>
 <li>
 Experience working in project-based teams, collaborating with colleagues, interacting with stakeholders, working to deadlines, and delivering projects that solve specific business problems.
 </li>
 <li>
 You&rsquo;re curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment &ndash; validating outputs and aligning with policies, risk standards, and ethical use.
 
 
 </li>
 </ul>
 
 About Us
 
 
 UBS is a leading and truly global wealth manager and the leading universal bank in Switzerland. We also provide diversified asset management solutions and focused investment banking capabilities. Headquartered in Zurich, Switzerland, UBS is present in more than 50 markets around the globe.
 
 
 We know that great work is never done alone. That&rsquo;s why we place collaboration at the heart of everything we do. Because together, we&rsquo;re more than ourselves. Want to find out more? Visit ubs.com/careers.
 
 
 
 Join us
 
 
 
 At UBS, we know that it's our people, with their diverse skills, experiences and backgrounds, who drive our ongoing success. We&rsquo;re dedicated to our craft and passionate about putting our people first, with new challenges, a supportive team, opportunities to grow and flexible working options when possible. Our inclusive culture brings out the best in our employees, wherever they are on their career journey. And we use artificial intelligence (AI) to work smarter and more efficiently. We also recognize that great work is never done alone. That&rsquo;s why collaboration is at the heart of everything we do. Because together, we&rsquo;re more than ourselves.
 
 
 We&rsquo;re committed to disability inclusion and if you need reasonable accommodation/adjustments throughout our recruitment process, you can always contact us.
 
 
 
 Disclaimer / Policy statements
 
 
 
 UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.
</div>

Junior Data Scientist

<div><div><div><div>United Kingdom</div>
</div><div><div>Business management, administration and support
</div></div><div><div>Investment Bank
</div></div><div>Job Reference #
<div>336118BR</div>
</div><div>City
<div>London</div>
</div><div>Job Type
<div>Full Time
</div></div><div>Your role
<div>Are you passionate about AI/ML, programming, and automation? Do you have technical expertise in design, software development, and modeling? Do you aspire to develop the next generation of AI business applications? 
 
As a Data Scientist, you will collaborate with our data science and business teams to build state-of-the-art models, and perform exploratory analysis on new and existing data to identify, investigate, and solve challenges. You should be comfortable applying a variety of techniques to find the best results and capable of researching new methods to trial. You will work closely within a small team where collaboration is key to achieving our common goals. 
 
<ul><li>Collaborate with the business to assess opportunities for AI/data analytics technologies and maximize their value/impact for our clients.</li><li>Support the design of AI/data analytics solution architecture and work with stakeholders to develop implementation roadmaps.</li><li>Support AI/data analytics solution implementation and deployment.</li><li>Develop, maintain, and deploy LLM, machine learning, and natural language processing pipelines and models with high performance, quality, and stability.</li><li>Partner with the business to integrate AI and machine learning solutions across various strategic platforms. Models may span across a variety of domains, including but not limited to: LLM-based agentic AI architectures, natural language processing (e.g., document classification, named entity recognition, topic modeling, advanced and semantic information search, extraction), data analytics (predictive modeling, time-series analytics, pattern recognition, recommendation engines), computer vision (OCR), and voice recognition (speech-to-text).</li><li>Research and build POCs for new and innovative AI solutions and technologies.</li></ul></div>
</div><div>Your team
<div>You&rsquo;ll be working in the IB AI Center of Excellence team in London, focusing on building AI products across the Investment Bank. The AI solutions we build support our colleagues in working more efficiently, reducing the risks we face as a bank, and generating more revenues. Moreover, our products ensure that our clients receive timely and personalized content. As a Data Scientist, you&rsquo;ll play an important role in shaping the AI landscape within the IB. 
 
Diversity helps us grow together. That&rsquo;s why we are committed to fostering and advancing diversity, equity, and inclusion. It strengthens our business and brings value to our clients.</div>
</div><div>Your expertise
<ul><li>Master's degree or higher in a quantitative / scientific field or equivalent work experience</li><li>Experience in designing and developing enterprise-scale AI and NLP solutions in the areas of Named Entity Recognition, Document Classification, Document Summarization, Topic Modeling, Sentiment Analysis, and OCR text processing.</li><li>Experience building ML &amp; NLP solutions using common ML libraries and frameworks, including Pandas, Sklearn, TensorFlow, SparkML, Pytorch, etc.</li><li>Skilled in end-to-end development of ML/NLP models (supervised &amp; unsupervised), including data cleaning, pipeline creation for structured/unstructured data, feature engineering, model selection/ensembles, evaluation metrics, visualization, and advanced statistical modeling (regression, spatial, time series).</li><li>Ideally 2+ years of programming experience in one or more of the following: Python, R, Scala, C/C++, Matlab, SQL/Postgres, etc. Knowledge of CI/CD pipelines, Git, and GitHub/GitLab.</li><li>Familiarity with Agentic AI frameworks such as LangGraph, AutoGen, etc is a plus</li><li>Experience working in project-based teams, collaborating with colleagues, interacting with stakeholders, working to deadlines, and delivering projects that solve specific business problems.</li><li>You&rsquo;re curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment &ndash; validating outputs and aligning with policies, risk standards, and ethical use.</li></ul>
</div><div>About us
<div>UBS is a leading and truly global wealth manager and the leading universal bank in Switzerland. We also provide diversified asset management solutions and focused investment banking capabilities. Headquartered in Zurich, Switzerland, UBS is present in more than 50 markets around the globe. 
We know that great work is never done alone. That&rsquo;s why we place collaboration at the heart of everything we do. Because together, we&rsquo;re more than ourselves. Want to find out more? Visit ubs.com/careers.</div>
</div><div>Join us
<div>At UBS, we know that it's our people, with their diverse skills, experiences and backgrounds, who drive our ongoing success. We&rsquo;re dedicated to our craft and passionate about putting our people first, with new challenges, a supportive team, opportunities to grow and flexible working options when possible. Our inclusive culture brings out the best in our employees, wherever they are on their career journey. And we use artificial intelligence (AI) to work smarter and more efficiently. We also recognize that great work is never done alone. That&rsquo;s why collaboration is at the heart of everything we do. Because together, we&rsquo;re more than ourselves. 
We&rsquo;re committed to disability inclusion and if you need reasonable accommodation/adjustments throughout our recruitment process, you can always contact us.</div>
</div><div>Disclaimer / Policy statements
<div>UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.</div></div></div></div><div></div>

<div>
 
 
 Department:
 
 Data &amp; AI
 
 
 
 Location:
 
 UK - London
 
 
 
 
 Description
 
 
 
 Insurance isn't the first industry most people think of when they imagine interesting data science work. That's exactly why this role is interesting.
 
 
 CFC's Data &amp; AI unit is building production agentic systems that automate complex underwriting decisions - not demos, not proof-of-concepts sitting on a shelf, but AI agents and Machine Learning (ML) pipelines that drive real business outcomes. The team includes machine learning engineers and software engineers shipping production services, and this role sits alongside them as an analytical counterpart: running experiments, stress-testing assumptions, and generating the evidence that shapes what gets built and how it improves over time.
 
 
 This is an Associate Data Scientist role designed for someone early in their career who wants genuine exposure to production AI systems from day one. You'll work closely with ML and AI engineers, contributing to discovery work that feeds directly into live services - statistical analysis, feature engineering, LLM evaluation, and the kind of careful, evidence-based thinking that makes the difference between an AI system that works in a notebook and one that holds up under real conditions.
 
 
 The problems are genuinely hard. The data is complex, the decisions are high-stakes, and the domain has the kind of depth that keeps the work interesting. If you want to grow quickly in applied AI and ML - working on real systems, not toy datasets - this is the right environment.
 
 
 
 About the role
 
 
 
 <ul>
 <li>
 Design and run experiments that directly shape production AI agents &mdash; testing ideas, validating approaches, and turning research into deployed improvements.
 </li>
 <li>
 Actively explore cutting-edge developments in AI and machine learning &mdash; with the space and support to experiment, prototype, and bring new techniques into production where they add value.
 </li>
 <li>
 Evaluate and refine LLM-powered workflows &mdash; building robust evaluation frameworks, stress-testing agent behaviour, and driving continuous quality improvements in live systems.
 </li>
 <li>
 Explore complex, real-world datasets to uncover insights that meaningfully improve underwriting decisions and system performance at scale.
 </li>
 <li>
 Prototype and iterate on features for AI/ML pipelines, taking ideas from early exploration through to measurable impact in production services.
 </li>
 <li>
 Investigate how agentic systems behave in production &mdash; identifying edge cases, failure modes, and opportunities to make systems more robust and reliable.
 </li>
 <li>
 Collaborate closely with ML/AI engineers to bridge research and production &mdash; contributing code, debugging issues, and helping ship improvements end-to-end.
 </li>
 <li>
 Document experiments, findings, and methodologies clearly so that insights are reproducible and decisions are traceable.
 
 
 </li>
 </ul>
 
 About you
 
 
 
 We are looking for a Junior Data Scientist who enjoys solving complex problems and turning data into meaningful, real‑world outcomes. In this role, you will work across the full analytical lifecycle, from exploring data and building machine learning models to shaping how insights are communicated and applied across the business. You also play a part in how we responsibly explore and apply emerging technologies such as LLMs, focusing on how they perform and deliver value in practice.
 
 
 You:
 <ul>
 <li>
 combine a strong grounding in statistics with hands‑on technical capability in Python and SQL
 </li>
 <li>
 take pride in producing clear, reliable analysis
 </li>
 <li>
 are thoughtful and detail‑driven, able to communicate effectively with a wide range of stakeholders, and comfortable learning from others while growing your own ownership
 </li>
 <li>
 bring curiosity, ask the right questions and look beneath the surface
 </li>
 <li>
 have experience with Azure, MLflow, or LLM tooling is a bonus, but not expected&mdash;we value mindset and approach just as highly as experience.
 
 
 </li>
 </ul>
 
 Core Values
 
 
 
 
 Love what you do:
 
 
 We show up each day ready to take on the world. Our passion and intensity set us apart and makes the difference to our colleagues, customers, brokers and carriers.
 
 
 
 Challenge everything:
 
 
 We&rsquo;re never afraid to question the way that things are done and we constantly challenge ourselves and others to makes things better.
 
 
 
 Have fun, be good:
 
 
 Insurance is a serious business, but we don&rsquo;t take ourselves too seriously. We make it fun to work at CFC, we welcome all viewpoints, and we treat everyone how we would expect to be treated.
</div>

Associate Data Scientist

Hiscox

<div>
 
 Job Type
 
 
 
 Permanent
 
 
 
 Build a brilliant future with Hiscox
 
 
 
 
 Reporting to: Re &amp; ILS Head of Data
 
 
 
 
 Location:
 
 London
 
 
 Type: Permanent
 
 
 
 Role Overview
 
 
 
 The Lead Data Scientist is a crucial member of the
 
 extended
 
 RE&amp;ILS Tech Leadership Team, responsible for building, leading, and nurturing a highly capable (New)
 
 Data Science and Machine Learning
 
 chapter.
 
 
 This role facilitates the successful delivery of new AI Cloud-based solutions against our growing list of business use cases (involving complex Data Analytics, Machine Learning, and AI Agent based solutions).
 
 
 You will co-lead the new Data Science chapter with the RE&amp;ILS Head of Data and help ensure its members provide Data Science capabilities and insights to support decision-making across RE&amp;ILS strategic Value Streams. Whilst the chapter grows, you are expected to be
 
 hands-on
 
 actively helping to architect, design, and build AI or Data Science-based solutions, using internally trained models, LLMs and/or a combination of both.
 
 
 Whilst undertaking this pioneering work it is essential that you and your entire chapter operates within the boundaries of the
 
 Group AI Governance Framework
 
 and maintains rigorous data governance standards. You will be accountable of this adherence.
 
 
 This is likely to be your first managerial role and the first time you have had one or more direct reports &ndash; having previously been a Senior Data Scientist or Machine Learning Engineer yourself. In this role you will be responsible for the management of a 1 to 4 junior and mid-level Hiscox FTEs and Partner resources too. You will be expected to support the Head of Data with attracting and retaining the best talent; helping to manage their career progression and ensure they are highly engaged, find the work fulfilling, and have the ability to rapidly deliver value to the business. As this is likely to be your first managerial role you will be supported and guided by other Data Leaders &ndash; Head of Data and the Hiscox Group Head of Data Science as well.
 
 
 
 About Hiscox Re &amp; ILS
 
 
 
 Hiscox Re &amp; ILS is located in
 
 Bermuda and London
 
 and underwrites reinsurance risks from around the world on behalf of our own and other people&rsquo;s capital. The team of over 100 smart, enthusiastic individuals are committed to providing top quality service to brokers and clients across a broad range of reinsurance products. Our approach is simple; match the best underwriting risk against globally diversified capital. Our proactive, product-led underwriting approach is complemented by a commitment to world class service and purpose-built analytics and systems. We know our people are our biggest asset so finding and retaining the best talent is critical to achieving our vision.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Chapter Leadership &amp; Talent Management
 </li>
 <li>
 People Management: Lead, recruit, mentor, coach, train, and retain a high-performing chapter of Data Scientists and Machine Learning Engineers (expected to grow to over the next few years), including both Hiscox FTE and Partner colleagues. Inspire chapter members to be curious, embrace new ideas, and nurture psychological safety to help build a high-performance culture.
 </li>
 <li>
 In this role you will manage at least one to two Hiscox data scientists and some partner resources too. You will be expected to manage their performance with relevant PDRs and help to calibrate their overall performance ratings with other people managers in the team. You will work with the Head of Data and Group Head of Data Science to help tailor the training needs to suit each individual and ensure they have the opportunity to grow and progress in their chosen career paths.
 </li>
 <li>
 Culture &amp; Development: Cultivate a collaborative, engaged, and fulfilled team culture. Provide technical leadership, career guidance, and direction to the team, ensuring successful delegation to all chapter members.
 </li>
 <li>
 Best Practice: Ensure the chapter adheres to best practices in data science, AI, and complex analytics, sharing knowledge across the wider Hiscox Analytics and Data community through active participation in Communities of Practice.
 </li>
 <li>
 Mentoring: Mentor and educate others in the various data science techniques, encouraging the team to continually learn &ndash; especially supporting the adoption of LLMs and proprietary models that could significantly accelerate our ability to deploy value.
 </li>
 <li>
 Solution Delivery &amp; ML Ops Excellence
 </li>
 <li>
 Hands-On Architecture: Get hands-on to help architect, design, and build complex models that integrate into existing IT solutions to improve data-driven decision-making throughout the Reinsurance Value Chain. Ensure you and your chapter members work closely with Platform Engineers and Architects to create the most optimal and safe solutions.
 </li>
 <li>
 ML Ops Platform: Actively work with the Head of Platform Engineering to establish and maintain a professional ML Ops platform to facilitate the effective support of developed models in production. This includes embedding a rigorous model evaluation process, ensuring consistent model refresh/rebuild capabilities due to model or data drift, and implementing effective monitoring and alerts against rogue behaviour.
 </li>
 <li>
 Speed of Execution: Empower the chapter to work effectively within autonomous squads, delivering desired and valuable outcomes in an incremental manner while correctly balancing accuracy, fast return on investment, and reliability. Understand when to move on and fail fast &ndash; as a lot of AI use cases will be highly experimental in nature with no guarantees of success.
 </li>
 <li>
 Pipeline Collaboration: Work with Data Engineering and other teams to properly understand and contribute to the requirements and building of necessary data pipelines/products consumed by our models.
 </li>
 <li>
 Strategy, Governance &amp; Innovation
 </li>
 <li>
 Use Case Identification: Continually work with key business leaders, the Head of Data and key stakeholders to identify new use cases and opportunities where data science/AI can deliver a competitive advantage or reduce waste/costs through efficiency gains.
 </li>
 <li>
 Governance &amp; Compliance: Champion data and model governance, working within the Group AI Governance Framework. Ensure a mature understanding of data governance, lineage, and version control, and enforce data privacy by design in all new work.
 </li>
 <li>
 Innovation: Maintain a strong awareness of new trends and techniques in Data Science, AI, and Machine Learning. Drive the identification of innovative data solutions and technologies, and actively undertake Proof of Concepts and R&amp;D to deliver reliable insights and potential next steps quickly.
 </li>
 <li>
 Communication: Ensure clear and effective communication of data science solutions and outcomes across business layers, technical teams, and senior leadership.
 
 
 
 </li>
 </ul>
 
 Required Experience And Structure
 
 
 
 <ul>
 <li>
 Reporting: Reports into the RE&amp;ILS Head of Data with a dotted line into the new Group Head of Data Science.
 </li>
 <li>
 Direct Reports: Direct line management for Data Scientists and Machine Learning Engineers within the RE&amp;ILS Data Science Chapter.
 </li>
 <li>
 Key Partners: RE&amp;ILS CTO, Group Head of Data Science, RE&amp;ILS Head of Data, Product Managers, Product Owners, and strategic partners (e.g. Google Cloud, Microsoft).
 
 
 
 </li>
 </ul>
 
 Candidate Profile
 
 
 
 The successful candidate will be an energetic, highly capable, and passionate Senior Data Scientist who wants to move into their first people management role. You will need to balance technical expertise with effective people management and strategic business partnership. You must be comfortable working in an FCA-regulated business, advocating for a data-driven approach, and driving innovation while maintaining rigorous AI governance standards. You will have a strong determination and resilience and not fear failure or the inevitable setbacks often found in highly experimental work.
 
 
 
 Main Experience Required Is
 
 
 
 <ul>
 <li>
 Deep Interest in Leadership: As an experienced data scientist or machine learning engineer, has previously demonstrated excellent traits in mentoring and coaching more junior team members and has been happy to invest in them - clearly demonstrating they care about other peoples&rsquo; career progression. Also you can evidence some successful business outcomes that you personally drove forward using advanced Data Science/AI &ndash; as this most likely is your first leadership role.
 </li>
 <li>
 Technical Depth: Extensive "hands-on" experience in architecting, designing, and building complex ML models, with a strong understanding of cloud services and the AI/ML/LLM ecosystem.
 </li>
 <li>
 ML Ops Maturity: Proven ability to build, maintain, and support production-deployed models, including establishing effective monitoring, evaluation, and refresh processes.
 </li>
 <li>
 AI and Data Governance: Mature understanding of AI and Data governance - data obfuscation &amp; data privacy laws, data version control, data lineage, and the application of AI governance frameworks in a regulated environment.
 </li>
 <li>
 Stakeholder Management: Experience in managing and driving collaboration with business unit leaders (Underwriters, pricing teams, MI team) and external technology partners like Google Cloud, Snowflake, DataIku and Microsoft.
 </li>
 <li>
 Education: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent.
 </li>
 <li>
 Capacity for independent, high-quality research and exploratory data analysis, with the ability to develop and apply novel methodologies to solve ill-defined and challenging business problems.
 </li>
 <li>
 Exceptional proficiency in Python (and R) for data science, coupled with SQL capabilities for data manipulation and extraction. Demonstrable mastery in a wide range of machine learning and statistical modelling techniques, from classical linear models and tree-based methods to advanced deep learning architectures.
 </li>
 <li>
 Real world experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs), AI Agents and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions.
 </li>
 <li>
 Demonstrate a Solid understanding of foundational statistics and experimental design. Pioneer the development and robust deployment of highly impactful machine learning and AI-driven solutions, directly contributing to significant commercial value, quantifiable business growth, or efficiency gains across the organization.
 </li>
 <li>
 Ability to translate complex data science insights into tangible, measurable improvements across critical business processes and key performance indicators, ensuring the real-world adoption and beneficial outcomes of our analytical work.
 </li>
 <li>
 Ability to elevate the technical maturity and capabilities of the data science chapter by shaping and implementing industry-leading AI, data, and analytics techniques, methodologies, and engineering best practices.
 </li>
 <li>
 Educator: shown the ability to train and coach more junior and mid-level team members - ensuring they have excellent career progression and become high performers.
 
 
 
 </li>
 </ul>
 If you are a visionary expert looking for your first leadership role and ready to accelerate our value delivery and champion all things Data Science and AI, we invite you to apply for the position of Lead Data Scientist at Hiscox Re &amp; ILS. Join our team and be a catalyst for AI adoption in a dynamic, forward-thinking organization.
 
 
 
 Work with amazing people and be part of a unique culture
 
</div>

Lead Data Scientist

Compare The Market

<div>Senior Data Scientist
Function: Data &amp; AI Solutions
 
Location: Hybrid, London or Peterborough office 
Curious about what&rsquo;s next?
 
So are we. Join Compare the Market and help to make financial decision making a breeze for millions.
At Compare the Market, we&rsquo;re a purpose-driven business powered by tech and AI. We&rsquo;re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.
We&rsquo;ve carved a meerkat-shaped niche and we&rsquo;re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you&rsquo;ll fit right in. 
We&rsquo;d love you to be part of our journey.
Compare the Market is shifting from a business that answers data questions to one that builds the intelligence powering our AI platform - signals detected, decisions shaped, actions triggered.
As a Senior Data Scientist in Data &amp; AI Solutions, you will lead the design and build of models and pipelines at the heart of our AI platform - from understanding how hundreds of insurance partners price risk, to predicting which customers need a better deal, to powering personalisation. Your job is to build the systems that surface answers that don&rsquo;t yet exist in the data.
We want someone who thinks in systems, with curiosity across the modern data science stack and depth in at least one area. We are actively developing agentic AI and want a Senior Data Scientist ready to deepen their expertise and contribute from a specific angle.
You will lead by doing, raising the bar for those around you and working closely with ML engineering, product, and commercial colleagues. 
Some of the great things you'll be doing:
<ul><li>Lead ML and analytics initiatives end-to-end, from exploration through to deployment and monitoring, collaborating with ML Engineers on productionisation
</li><li>Translate business and customer problems into structured, measurable ML solutions
</li><li>Design and interpret experiments and A/B tests with scientific rigour
</li><li>Champion responsible, auditable AI - owning model performance in production, knowing when a system is degrading and how to address it, in a regulated financial services environment where precision and explainability matter
</li><li>Navigate the tooling landscape: knowing when classical ML is right, when an LLM adds value, when an agentic approach is needed
</li><li>Work with commercial, product, and engineering colleagues to scope and prioritise work, communicating outcomes clearly
</li>Mentor junior data scientists and contribute to standards across the wider Data &amp; AI Solutions chapter 
<li>
</li></ul>What we'd like to see from you:
The Essentials
<ul><li>Proven experience delivering ML solutions with measurable business impact
</li><li>Strong Python and modelling fundamentals - supervised and unsupervised methods, statistical analysis, feature engineering
</li><li>A track record of taking models to production and owning their performance: monitoring, degradation, retraining
</li><li>Ability to collaborate effectively with engineering teams on deployment and ML lifecycle
</li>Clear communication - able to make technical work legible to commercial and product audiences 
<li>
</li></ul>Highly Valued
<ul><li>Hands-on experience with LLM-based systems: prompt engineering, RAG, tool use, or orchestration frameworks such as LangChain or LangGraph
</li><li>Familiarity with multi-step agentic AI patterns
</li><li>Experience in financial services or another regulated sector
</li><li>MLflow, model registries, or similar ML lifecycle tooling
</li>Exposure to cloud ML platforms - GCP Vertex AI, AWS SageMaker, or equivalent 
<li>
</li></ul>Why Compare the Market?
We&rsquo;re a business built for pace and performance. Here, you&rsquo;ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress.
We believe diverse teams make better decisions, and we&rsquo;re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive.
If you&rsquo;re ready to stretch yourself, raise the bar, and grow with a team that&rsquo;s serious about performance, innovation, and purpose, we&rsquo;d love to hear from you.</div>

Senior Data Scientist

Compare the Market

<div>
 
 Job Description
 
 
 
 
 Data Scientist
 
 
 
 
 Function:
 
 Data
 
 
 
 Location:
 
 Hybrid, London
 
 
 
 Curious about what&rsquo;s next?
 
 
 
 So are we. Join Compare the Market and help to make financial decision making a breeze for millions.
 
 
 At Compare the Market, we&rsquo;re a purpose-driven business powered by tech and AI. We&rsquo;re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.
 
 
 We&rsquo;ve carved a meerkat-shaped niche and we&rsquo;re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you&rsquo;ll fit right in.
 
 
 
 We&rsquo;d love you to be part of our journey.
 
 
 
 As a Data Scientist at Compare the Market, you&rsquo;ll play a key role in developing AI and machine learning solutions that improve customer journeys, pricing intelligence, and product personalisation. Working cross functionally alongside engineers, analysts, and product managers contributing to real-world applications of machine learning that impact millions.
 
 
 
 Some Of The Great Things You&rsquo;ll Be Doing
 
 
 
 
 AI Solution Delivery
 
 
 
 <ul>
 <li>
 Contribute to the development of machine learning solutions from design through to deployment
 </li>
 <li>
 Build and evaluate predictive models using Python and SQL
 </li>
 <li>
 Translate business challenges into structured data science problems
 
 
 </li>
 </ul>
 
 Applied Science &amp; Experimentation
 
 
 
 <ul>
 <li>
 Conduct statistical analysis and feature engineering to generate actionable insights
 </li>
 <li>
 Support A/B test design, evaluation, and interpretation with rigour and clarity
 </li>
 <li>
 Collaborate with stakeholders to ensure data science solutions are well aligned to product and business needs
 
 
 </li>
 </ul>
 
 Platform &amp; Practices
 
 
 
 <ul>
 <li>
 Work with ML Engineers to support deployment, monitoring, and performance tracking of your models
 </li>
 <li>
 Contribute to team standards on reproducibility, documentation, and model evaluation
 </li>
 <li>
 Apply responsible AI practices to ensure fairness and transparency
 
 
 </li>
 </ul>
 
 Team &amp; Learning
 
 
 
 <ul>
 <li>
 Take part in peer reviews, knowledge sharing, and internal learning sessions
 </li>
 <li>
 Support and coach junior team members and peers, contributing to their growth
 </li>
 <li>
 Play an active role in shaping our data science culture and community
 
 
 </li>
 </ul>
 
 What We&rsquo;d Like To See From You
 
 
 
 
 Must Have
 
 
 
 <ul>
 <li>
 Experience delivering machine learning or advanced analytics solutions with measurable impact
 </li>
 <li>
 Proficient in Python and SQL, with practical experience in modelling, feature engineering, and evaluation
 </li>
 <li>
 Strong problem-solving skills and ability to break down complex problems into data-driven approaches
 </li>
 <li>
 Comfortable working collaboratively in cross-functional teams
 </li>
 <li>
 Clear communicator with a passion for sharing insights and learning from others
 </li>
 <li>
 A background in a quantitative discipline (e.g. Computer Science, Mathematics, Statistics, Engineering) or equivalent hands-on experience in applied machine learning
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience working in regulated sectors such as insurance, banking, or financial services
 </li>
 <li>
 Familiarity with tools like MLflow, model registries, or experimentation platforms
 </li>
 <li>
 Understanding of basic CI/CD concepts or exposure to production ML workflows
 </li>
 <li>
 Interest in generative AI or large language models (e.g. OpenAI, Vertex AI)
 </li>
 <li>
 Awareness of responsible AI principles, such as fairness or explainability in models
 
 
 </li>
 </ul>
 
 Why Compare the Market?
 
 
 
 We&rsquo;re a business built for pace and performance. Here, you&rsquo;ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress.
 
 
 We believe diverse teams make better decisions, and we&rsquo;re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive.
 
 
 If you&rsquo;re ready to stretch yourself, raise the bar, and grow with a team that&rsquo;s serious about performance, innovation, and purpose, we&rsquo;d love to hear from you.
</div>

Data Scientist

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