lead scientist

Data Idols

<div><h2 class="jobSectionHeader"><b>Lead Data Scientist &ndash; Commercial</b></h2>
<h3 class="jobSectionHeader"><b>&pound;95,000 &ndash; &pound;105,000</b></h3>
<h3 class="jobSectionHeader"><b>London hybrid</b></h3>
<p>
At Data Idols, we are working with a fast-growing, technology-led digital business operating at significant scale across multiple international markets. They are now looking for a Lead Data Scientist to play a key role in developing commercially impactful data science solutions across a critical business domain.</p>
<h3 class="jobSectionHeader"><b>
The Opportunity</b></h3>
<p>
This is a high-ownership leadership role sitting at the intersection of data science, commercial strategy and operational performance. You will act as a key data science partner for a core business function, helping stakeholders understand performance, identify optimisation opportunities and make better strategic decisions through data.</p>
<p>
You will take ownership of the development of machine learning models, predictive analytics and experimentation frameworks that directly support commercial outcomes. Working closely with commercial, product, analytics and engineering teams, you will apply data science to areas such as customer behaviour, forecasting, segmentation, propensity modelling, churn, pricing and optimisation.</p>
<p>
You will help shape how data science is delivered across the organisation, setting standards for modelling, measurement and experimentation, and ensuring insight translates into meaningful commercial impact. This is a high-impact role where your work will influence both day-to-day decision-making and longer-term strategic direction.</p>
<h3 class="jobSectionHeader"><b>
Skills and experience</b></h3>
<ul><li>Experience building and deploying production machine learning models</li>
<li>Strong Python and modern data science tooling experience</li>
<li>Experience working closely with commercial, product or operational stakeholders</li>
<li>Ability to influence strategic decision-making through data science and insight</li>
</ul>
<p>If you are looking for a new challenge and want to play a key role in shaping commercial and operational decision-making through data science, please submit your CV for initial screening and further details.</p>
<h3 class="jobSectionHeader"><b>
Lead Data Scientist &ndash; Commercial</b></h3></div><div></div>

Lead Data Scientist

Altak Group Inc.

<div>
 <p>
  <strong>
   Job Title: Lead Data Scientist &ndash; Healthcare (AI Architecture Focus)
  </strong>
 </p>
 <p>
  <strong>
   Location: EAST coast (REMOTE)
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Required Qualifications
  </strong>
 </p>
 <p>
  &bull; 7+ years of experience in data science, with recent experience in a Lead Data
 </p>
 <p>
  Scientist or similar senior role.
 </p>
 <p>
  &bull; Strong experience working in the healthcare domain (payer, provider, life
 </p>
 <p>
  sciences, digital health, or health tech).
 </p>
 <p>
  &bull; Hands-on experience designing and deploying ML models in production
 </p>
 <p>
  environments.
 </p>
 <p>
  &bull; Solid understanding of AI architecture concepts, including scalable ML
 </p>
 <p>
  systems, MLOps, and cloud-based deployments.
 </p>
 <p>
  &bull; Proficiency in Python and common ML libraries (e.g., scikit-learn, TensorFlow,
 </p>
 <p>
  PyTorch).
 </p>
 <p>
  &bull; Experience with SQL and big data technologies (e.g., Spark, Databricks,
 </p>
 <p>
  Snowflake).
 </p>
 <p>
  &bull; Strong understanding of data modeling, statistics, and machine learning
 </p>
 <p>
  algorithms.
 </p>
 <p>
  &bull; Experience working in cloud environments such as AWS, Azure, or GCP.
 </p>
 <p>
  &bull; Excellent communication skills with the ability to explain complex technical
 </p>
 <p>
  concepts to non-technical stakeholders.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Preferred Qualifications
  </strong>
 </p>
 <p>
  &bull; Prior experience collaborating closely with or acting as an AI Architect on
 </p>
 <p>
  enterprise-scale solutions.
 </p>
 <p>
  &bull; Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow,
 </p>
 <p>
  SageMaker, Azure ML).
 </p>
 <p>
  &bull; Familiarity with NLP, computer vision, or generative AI use cases in healthcare.
 </p>
 <p>
  &bull; Knowledge of healthcare interoperability standards such as HL7, FHIR, or ICD
 </p>
 <p>
  codes.
 </p>
 <p>
  &bull; Experience leading cross-functional teams in a contract or consulting
 </p>
 <p>
  environment.
 </p>
</div>


1st Central

<div>
 <p>
  <strong>
   At 1st Central, everything starts with our people.
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  As one of the UK&rsquo;s leading motor and home insurers, we use smart technology, data and great service to make insurance fast, fair and simple for over 1.4 million customers. We&rsquo;re proud to create an environment where people feel supported, trusted and able to grow - whether that&rsquo;s developing new skills, taking on fresh challenges or making a real impact every day. If you&rsquo;re looking for a role where you can make a difference, we&rsquo;d love to hear from you.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We&rsquo;re looking for a
  <strong>
   Lead Data Scientist
  </strong>
  to join a team of data scientists and specialists, helping to deliver a portfolio of innovative services that unlock value from the company&rsquo;s extensive information assets. In this role, you&rsquo;ll apply advanced data science techniques, both independently and collaboratively, to uncover insights and drive business value. As a senior member of the team, you&rsquo;ll also play a key role in mentoring and upskilling colleagues.
 </p>
 <p>
  <br/>
 </p>
 <p>
  You&rsquo;ll work with large volumes of data from a variety of sources, including structured and unstructured datasets. Using strong critical thinking and problem-solving skills, you&rsquo;ll analyse and interpret data, build predictive models, and develop machine learning algorithms to generate actionable insights.
 </p>
 <p>
  <br/>
 </p>
 <p>
  As the Lead Data Scientist, you&rsquo;ll be responsible for proposing solutions to business challenges and partnering with cross-functional teams to implement them. Recognising the dependencies Group companies have on technology provided in-house, you&rsquo;ll collaborate closely with in-house technology providers, as well as data presentation and delivery teams across multiple locations, to ensure seamless and effective outcomes.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We&rsquo;re big on
  <strong>
   flexible hybrid working
  </strong>
  . Our teams are based across
  <strong>
   Haywards Heath (West Sussex)
  </strong>
  and
  <strong>
   Salford Quays (Manchester).
  </strong>
  We primarily work from home but value collaboration, so we come together in person to keep ideas flowing, typically once a quarter. Prefer being in the office more often? That works for us too.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Core skills we&rsquo;re looking for to succeed in the role:
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   <strong>
    Analytical &amp; Technical Skills:
   </strong>
   Proven analytical and statistical modelling skills
  </li>
  <li>
   <strong>
    Technical Skills:
   </strong>
   Familiarity with data science tools and programming languages (e.g.
   <strong>
    Python
   </strong>
   )
  </li>
  <li>
   <strong>
    Machine Learning:
   </strong>
   Ability to build and train Machine Learning models
  </li>
  <li>
   <strong>
    Professional Experience:
   </strong>
   Current Data Science experience, with
   <strong>
    Insurance
   </strong>
   industry exposure, highly advantageous
  </li>
  <li>
   <strong>
    Organisation &amp; Time Management:
   </strong>
   Strong time-management and organisational skills
  </li>
  <li>
   <strong>
    Education &amp; Qualifications:
   </strong>
   Degree in Data Science or other quantitative field
  </li>
  <li>
   <strong>
    Communication &amp; Stakeholder Management Skills:
   </strong>
   Strong verbal and written communication skills, with proven experience engaging and influencing stakeholders at all levels.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Why not check out the full job profile on our career pages and apply today
 </p>
</div>


Hiscox

<div>
 <strong>
  Job Type
  <br/>
  <br/>
 </strong>
 Permanent
 <br/>
 <br/>
 <strong>
  Build a brilliant future with Hiscox
  <br/>
  <br/>
 </strong>
 <strong>
  Reporting to: Re &amp; ILS Head of Data
  <br/>
  <br/>
 </strong>
 <strong>
  Location:
 </strong>
 London
 <br/>
 <br/>
 Type: Permanent
 <br/>
 <br/>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 The Lead Data Scientist is a crucial member of the
 <strong>
  extended
 </strong>
 RE&amp;ILS Tech Leadership Team, responsible for building, leading, and nurturing a highly capable (New)
 <strong>
  Data Science and Machine Learning
 </strong>
 chapter.
 <br/>
 <br/>
 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).
 <br/>
 <br/>
 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
 <strong>
  hands-on
 </strong>
 actively helping to architect, design, and build AI or Data Science-based solutions, using internally trained models, LLMs and/or a combination of both.
 <br/>
 <br/>
 Whilst undertaking this pioneering work it is essential that you and your entire chapter operates within the boundaries of the
 <strong>
  Group AI Governance Framework
 </strong>
 and maintains rigorous data governance standards. You will be accountable of this adherence.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 <strong>
  About Hiscox Re &amp; ILS
  <br/>
  <br/>
 </strong>
 Hiscox Re &amp; ILS is located in
 <strong>
  Bermuda and London
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <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.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Experience And Structure
  <br/>
  <br/>
 </strong>
 <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).
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Candidate Profile
  <br/>
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  Main Experience Required Is
  <br/>
  <br/>
 </strong>
 <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.
   <br/>
   <br/>
   <br/>
  </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.
 <br/>
 <br/>
 <em>
  Work with amazing people and be part of a unique culture
 </em>
</div>


Lloyds Banking Group

<div><p><b>End Date
</b></p>Wednesday 29 July 2026
<p></p><p><b>Salary Range
</b></p>&pound;92,701 - &pound;109,060
<p></p><p><b>We support flexible working &ndash; click here for more information on flexible working options
</b></p><p></p><p><b>Flexible Working Options
</b></p>Hybrid Working, Job Share
<p></p><p><b>Job Description Summary
</b></p>.
<p></p><p><b>Job Description
</b></p><div><div><p><b>JOB TITLE: </b>Lead Data Scientist
</p></div><div><p><b>SALARY: </b>&pound;92,701 - &pound;109,060
</p></div><div><p><b>LOCATION: </b>Edinburgh, Leeds, Manchester &amp; Bristol
</p></div><div><p><b>HOURS: </b>Full time (35 hours)
</p></div><div><p><b>WORKING PATTERN: </b>Our work style is hybrid, which involves spending at least two days per week, or 40% of our time, at one of our office sites. Colleagues with disabilities can be supported with workplace adjustments including hybrid working expectations in line with our Flexibility Works policy.<br>
</p></div><p></p><div><p><b>About this opportunity&hellip;
</b></p></div><div><p>At Lloyds Banking Group, we&rsquo;re moving to the next stages of our digital transformation, and it&rsquo;s our job within the Chief Security Office (CSO) to ensure that we keep our customers, colleagues and assets safe from threat. The CSO&rsquo;s Security Data and AI lab have a phenomenal opportunity for an experienced and dynamic Lead Data Scientist to work with our Analytics and Data Engineering feature teams.<br>
</p></div><p></p><div><p>In this role, you&rsquo;ll be owning the way in transforming how we detect, mitigate, and prevent cyber threats using advanced AI and machine learning. This is a rare opportunity to build the future of cybersecurity in one of the UK&rsquo;s most data-rich environments.<br>
</p></div><p></p><div><p><b>About us&hellip;
</b></p></div><div><p>Like the modern Britain we serve, we&rsquo;re evolving. Investing billions in our people, data and tech to transform the way we meet the ever-changing needs of our 26 million customers. We&rsquo;re growing with purpose. Join us on our journey and you will too&hellip;<br>
</p></div><p></p><div><p><b>What </b><b>you&rsquo;ll </b><b>do...
</b></p></div><div><ul><li><p>Own the delivery of security outcomes , including d efin ing and evolv ing approaches to anomaly detection that balanc e performance, explainability, and operational risk .
</p></li></ul></div><div><ul><li><p>Lead a team of Data Scientists
</p></li></ul></div><div><ul><li><p>Drive innovation in LLM-based security automation, including prompt engineering, RAG pipelines, and fine-tuning of models.
</p></li></ul></div><div><ul><li><p>Collaborate with Data Engineers to build scalable, secure, and production-ready ML pipelines on GCP.
</p></li></ul></div><div><ul><li><p>Partner with cyber defence, risk, and compliance teams to ensure models are explainable, ethical, and aligned with regulatory standards (e.g. SOC2, SWIFT, SOX).
</p></li></ul></div></div><div><div><ul><li><p>C ontribute to the Data Science Community of Practice, helping shape best practices across the organisation.
</p></li></ul></div><div><ul><li><p>Translate sophisticated data insights into actionable intelligence for collaborators across the Group COO and CSO functions<br>
</p></li></ul></div><p></p><div><p><b>What </b><b>you&rsquo;ll </b><b>need...
</b></p></div><div><ul><li><p>Confirmed experience in leading data science projects in cybersecurity, fraud, or behavioural analytics.
</p></li></ul></div><div><ul><li><p>Data Engineering - Deep expertise in Python, ML frameworks (e.g. TensorFlow, PyTorch ), and cloud platforms (preferably GCP).
</p></li></ul></div><div><ul><li><p>Deep Learning Theory &amp; Applications - Strong grasp of anomaly detection, time-series modelling, and deep learning architectures.
</p></li></ul></div><div><ul><li><p>Experience with LLMs and generative AI in production environments is highly desirable.
</p></li></ul></div><div><ul><li><p>Artificial Intelligence Ethics - A passion for ethical AI, model governance, and secure ML operations.
</p></li></ul></div><div><ul><li><p>Excellent communication and customer engagement skills
</p></li></ul></div><div><ul><li><p>Innovators Mentality - An innovator and change agent who keeps up to date with the latest trends and developments in data engineering and cyber security to ensure our strategies remain at the forefront of the industry.<br>
</p></li></ul></div><p></p><div><p><b>It would be great if you also had&hellip;
</b></p></div><div><ul><li><p>Understanding of the emerging threats within Cyber Security<br>
</p></li></ul></div><p></p><div><p><b>About working for us
</b></p></div><div><p>Our focus is to ensure we're inclusive every day, building an organisation that reflects modern society and celebrates diversity in all its forms. We want our people to feel that they belong and can be their best, regardless of background, identity or culture. We were one of the first major organisations to set goals on diversity in senior roles, create a menopause health package, and a dedicated Working with Cancer initiative. And it&rsquo;s why we especially welcome applications from under-represented groups. We&rsquo;re disability confident. So, if you&rsquo;d like reasonable adjustments to be made to our recruitment processes, just let us know.<br>
</p></div><p></p><div><p><b>We also offer a wide-ranging benefits package, which includes&hellip;
</b></p></div><div><ul><li><p>A generous pension contribution of up to 15%
</p></li></ul></div><div><ul><li><p>An annual bonus award, subject to Group performance
</p></li></ul></div></div><div><div><ul><li><p>Share schemes including free shares
</p></li></ul></div><div><ul><li><p>Benefits you can adapt to your lifestyle, such as discounted shopping
</p></li></ul></div><div><ul><li><p>30 days&rsquo; holiday, with bank holidays on top
</p></li></ul></div><div><ul><li><p>A range of wellbeing initiatives and generous parental leave policies<br>
</p></li></ul></div><p></p><div><p>If you&rsquo;re excited by the thought of becoming part of our team, get in touch. <b>We&rsquo;d </b><b>love to hear from you!
</b></p></div></div><p></p><p><b>At Lloyds Banking Group, we're driven by a clear purpose; to help Britain prosper. Across the Group, our colleagues are focused on making a difference to customers, businesses and communities. With us you'll have a key role to play in shaping the financial services of the future, whilst the scale and reach of our Group means you'll have many opportunities to learn, grow and develop.
</b></p><p></p><p><b>We keep your data safe. So, we'll only ever ask you to provide confidential or sensitive information once you have formally been invited along to an interview or accepted a verbal offer to join us which is when we run our background checks. We'll always explain what we need and why, with any request coming from a trusted Lloyds Banking Group person.
</b></p><p></p><p><b>We're focused on creating a values-led culture and are committed to building a workforce which reflects the diversity of the customers and communities we serve. Together we&rsquo;re building a truly inclusive workplace where all of our colleagues have the opportunity to make a real difference.</b></p></div>

Brego

<div><p>Brego is an automotive technology company using AI and data analytics to help dealerships, lenders, and other industry partners make better vehicle valuation, pricing, and risk decisions. Working at the intersection of software, data, and decision-making, the team focuses on turning complex information into practical products that support smarter outcomes across the automotive market.</p><p></p><p>
As a Lead Data Scientist, you will take ownership of the AI (custom neural networks rather than third-party LLM technology) and machine learning capabilities behind products that influence high-value pricing and risk decisions. This is a hands-on technical leadership role where you will be responsible for designing, building, deploying, and continuously improving production machine learning systems from end to end. You will own the full lifecycle of models, from feature engineering and training through deployment, monitoring, retraining, and ongoing optimisation, working independently while collaborating closely with engineering and product teams to deliver measurable business impact.</p><p></p>
Responsibilities<ul><li>
Own the end-to-end lifecycle of production machine learning models, from problem definition through deployment and ongoing optimisation.</li><li>
Design, build and deploy artificial neural network and machine learning models for vehicle valuation, pricing and other analytics.</li><li>
Take responsibility for production model performance, reliability and long-term maintenance.</li><li>
Evaluate model performance and improve predictive accuracy across production models.</li><li>
Develop and maintain automated retraining pipelines to keep models effective over time.</li><li>
Monitor deployed models, investigate issues and implement improvements to ensure models remain accurate and reliable.</li><li>
Design and run experiments, track results and use data to drive model improvements.</li><li>
Work closely with engineering and product teams to integrate models into production systems and deliver business value.</li></ul><br>
<b>
Requirements</b><p><br>
Must have:</p><ul><li>
5+ years of experience building and deploying machine learning models in production environments.</li><li>
Strong experience developing and training neural networks for real-world applications.</li><li>
Strong experience with the Python data science ecosystem, including pandas, NumPy and scikit-learn.</li><li>
Hands-on experience with PyTorch or TensorFlow.</li><li>
Strong understanding of machine learning, statistics, and model evaluation methodologies.</li><li>
Experience taking machine learning models from concept through deployment and ongoing production ownership.</li><li>
Experience evaluating model performance, improving predictive accuracy, and maintaining retraining pipelines, model monitoring, and experiment tracking.</li><li>
Experience with feature engineering and working with large, real-world datasets.</li><li>
Experience writing clean, maintainable, production-quality Python code.</li><li>
Experience with SQL for data analysis and data manipulation.</li><li>
Experience deploying ML workloads in cloud environments.</li><li>
Ability to independently own technical projects and make sound engineering decisions with minimal supervision.</li><li>
Strong problem-solving skills with the ability to investigate complex data and modelling challenges.</li><li>
Strong communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders.</li><li>
Experience collaborating with software engineers, product managers, and data engineers.</li><li>
Eligible to work in the UK.</li></ul><p></p><p>
Nice to have:</p><ul><li>
Experience in the automotive industry or with vehicle data.</li><li>
Experience in pricing, forecasting, risk modelling, or other predictive analytics domains.</li><li>
Experience with MLOps tooling and infrastructure.</li><li>
Experience building automated data and model pipelines.</li><li>
Experience mentoring or providing technical leadership to other data scientists or engineers.</li></ul><br>
<b>
Benefits</b><br>
<ul><li>
Competitive salary of &pound;90,000 - &pound;110,000 per year, depending on experience.</li><li>
Private healthcare.</li><li>
Pension scheme.</li><li>
Fully remote role with flexible working hours.</li><li>
Working from home allowance.</li><li>
Choice of Apple MacBook Pro or high-spec Windows workstation.</li><li>
Learning and progression opportunities.</li><li>
Optional access to our Silverstone office. The team usually meets there around one day per week, but attendance is entirely optional.</li><li>
High levels of ownership and autonomy with the opportunity to shape the company&rsquo;s AI strategy.</li><li>
Collaborative, low-bureaucracy engineering culture that values autonomy, integrity and innovation.</li><li>
Regular company social events.</li><li>
25 days annual leave plus 3 additional days between Christmas and New Year.</li></ul></div>

Smarsh

<div><div><b>Who are we?</b></div><div></div><div><br>
Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.</div><div></div><div><b><br>
Summary</b></div>
<div></div>
<div>As a <b>Lead Data Scientist (NLP &amp; Financial Compliance)</b> at <b>Smarsh</b>, you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM) solutions that power next-generation compliance and surveillance systems. You&rsquo;ll work on highly specialized problems at the intersection of<b> natural language processing</b>, <b>communications intelligence</b>, <b>financial supervision</b>, and <b>regulatory compliance</b>, where unstructured data from emails, chats, voice transcripts, and trade communications hold the keys to uncovering misconduct and risk.</div>
<div></div>
<div>The role will involve working with other Senior Data Scientists and mentoring Associate Data Scientists in analyzing complex data, generating insights, and creating solutions as needed across a variety of tools and platforms. This role demands both <b>technical excellence</b> in NLP modeling and a <b>deep understanding of financial domain behavior</b>&mdash;including insider trading, market manipulation, off-channel communications, MNPI, bribery, and other supervisory risk areas. The ideal candidate for this position will possess the ability to perform both independent and team-based research and generate insights from large data sets with a hands-on/can do attitude of servicing/managing day to day data requests and analysis.</div>
<div></div>
<div>This role also offers a unique opportunity to get exposure to many problems and solutions associated with taking machine learning and analytics research to production. On any given day, you will have the opportunity to interface with business leaders, machine learning researchers, data engineers, platform engineers, data scientists and many more, enabling you to level up in true end-to-end data science proficiency.</div>
<h3 class="jobSectionHeader"><b>How will you contribute?</b></h3><ul>
<li>Collect, analyze, and interpret small/large datasets to uncover meaningful insights to support the development of statistical methods / machine learning algorithms.</li>
<li>Lead the <b>design, training, and deployment of NLP and transformer-based models</b> for financial surveillance and supervisory use cases (e.g., misconduct detection, market abuse, trade manipulation, insider communication).</li>
<li>Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities</li>
<li>Data annotation and quality review</li>
<li>Exploratory data analysis and model fail state analysis</li>
<li>Contribute to model governance, documentation, and explainability frameworks aligned with internal and regulatory AI standards.</li>
<li>Client/prospect guidance in machine learning model and analytic fine-tuning/development processes</li>
<li>Provide guidance to junior team members on model development and EDA</li>
<li>Work with Product Manager(s) to intake project/product requirements and translate these to technical tasks within the team&rsquo;s tooling, technique and procedures</li>
<li>Continued self-led personal development</li>
</ul><h3 class="jobSectionHeader"><b>What will you bring?</b></h3><ul>
<li>Strong understanding of <b>financial markets, compliance, surveillance, supervision, or regulatory technology</b></li>
<li>Experience with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse</li>
<li>Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc&hellip;)</li>
<li>Strong knowledge of key programming concepts (e.g. split-apply-combine, data structures, object-oriented programming)</li>
<li>Solid statistics knowledge (hypothesis testing, ANOVA, chi-square tests, etc&hellip;)</li>
<li>Knowledge of NLP transfer learning, including word embedding models (gloVe, fastText, word2vec) and transformer models (Bert, SBert, HuggingFace, and GPT-x etc.)</li>
<li>Experience with natural language processing toolkits like NLTK, spaCy, Nvidia NeMo</li>
<li>Knowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and Kubernetes</li>
<li>Familiarity with Deep Learning techniques for NLP.</li>
<li>Familiarity with LLMs - using ollama &amp; Langchain</li>
<li>Excellent verbal and written skills</li>
<li>Proven collaborator, thriving on teamwork</li>
</ul>
<div></div><div><b>Preferred Qualifications</b></div>
<ul><li>Master&rsquo;s or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field</li>
<li>Familiarity with cloud computing platforms (AWS, GCS, Azure)</li>
<li>Experience with automated supervision/surveillance/compliance tools</li>
</ul><div></div>
<div>The above salary range represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting. <b><i>Any applicable bonus programs will be discussed during the recruiting process.</i></b></div>
<div></div>
<div>The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training.</div>
<div></div>
<div>Local cost of living assessments are done for each new hire at the time of offer.</div><div><b>
About our culture</b></div><div></div><div><br>
Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world&rsquo;s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.</div></div>

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