data science engineer

Worldpay

<div><p><b>Ready to take your career global?</b></p><p>
Make your mark at one of the biggest names in payments.</p><p>
We are seeking an experienced <b>Senior ML Software Engineer</b> to join our Data Science Enablement team. You will be the primary software engineering expert for a product area, working as part of a cross-functional agile team and owning the successful launches and ongoing operations of high-profile products in production. Your focus will be on driving new feature delivery, maintaining operational excellence, and collaborating on enhancements to our shared ML platform. You will work closely with cross-functional collaborators&mdash;including ML research engineers, product managers, and platform engineers&mdash;to deliver scalable, reliable, and low-latency ML solutions.</p><p>
In addition to technical expertise, this job requires strong collaboration skills.</p><p></p><p><b>
What you&rsquo;ll own</b></p><p>
Feature Development &amp; Delivery:</p><ul><li>
Design, implement, and deploy new features and enhancements to ML products, collaborating with Product and ML Research teams to refine requirements.</li></ul><p>
Technical Ownership and Stewardship:</p><ul><li>
Technical ownership of existing and new production ML products in your area, ensuring alignment of technical investments with business goals (in collaboration with a product owner) and engineering best practices.</li><li>
End-to-end technical stewardship of ML products, ensuring ongoing reliability and performance.</li></ul><p>
Contribute to ML platform:</p><ul><li>
Contribute to the evolution of the shared ML platform alongside other engineers to drive best practices and shared tooling across all products.</li></ul><p>
Operational Excellence:</p><ul><li>
Maintain and improve automated CI/CD pipelines, testing frameworks, and monitoring/logging, ensuring high operational standards.</li><li>
Conduct comprehensive code reviews to enforce coding standards, improve code quality, and share knowledge.</li></ul><p>
Continuous Improvement:</p><ul><li>
Identify and implement opportunities for process, tooling, and system improvements, proactively addressing technical debt and scaling challenges.</li></ul><p>
Release Management:</p><ul><li>
Oversee pre-release testing, coordinate releases and ensure smooth enablement of new features.</li></ul><p>
Leadership:</p><ul><li>
Provide technical guidance and support to other engineers and data scientists to solve complex technical challenges.</li><li>
Mentor and coach other engineers, supporting their professional growth.</li><li>
Foster a culture of collaboration, continuous improvement, and knowledge sharing.</li></ul><p>
Act Like an Owner:</p><ul><li>
Proactively identify and resolve blockers, navigate processes, and independently seek out information and connect with relevant teams to drive solutions in the face of ambiguity.</li><li>
Operate with a strong sense of urgency, consistently prioritizing and executing tasks to meet timelines and deliver results.</li></ul><p></p><p><b>
What you&rsquo;ll bring</b></p><ul><li>
5+ years as an ML-focused software engineer, ML Engineer, MLOps Engineer, or similar, with hands-on production experience</li><li>
Proven expertise with ML model deployment, API design, and integration into production environments</li><li>
Strong Python programming and relevant ML/data libraries</li><li>
Experience with containerization, orchestration, and AWS cloud services</li><li>
Building and operating CI/CD pipelines</li><li>
Monitoring, troubleshooting, and optimizing production ML systems</li><li>
Pre-release testing and release management</li><li>
Demonstrated ability to work independently, navigate ambiguity, and deliver results</li><li>
Excellent communication skills and ability to collaborate both within engineering organizations and on cross-functional teams</li><li>
Experience with OpenAPI, FastAPI, or similar</li></ul><p></p><p><b>
It&rsquo;s a bonus if you have</b></p><ul><li>
Experience with MLFlow, model versioning, and storage</li><li>
Familiarity with Databricks or similar platforms</li><li>
Experience supporting high-volume, real-time data products</li><li>
Automated testing and validation frameworks</li><li>
Experience designing and configuring low-latency databases to serve real-time features, such as DynamoDB</li><li>
Experience with Terraform Cloud</li><li>
Experience in large companies, mature engineering teams, and/or highly regulated industries</li><li>
AI-assisted coding experience (e.g. GitHub Copilot)</li></ul><p></p><p><b>
Why Join Us?</b></p><ul><li>
Impact: Play a key role as the technical owner of high-profile ML products delivering meaningful business impact to merchants and advancing key pillars of the company&rsquo;s strategy. Your work will directly influence the reliability, scalability, and evolution of critical production systems.</li><li>
Autonomy: Take end-to-end technical ownership of your product area, with the freedom and responsibility to drive technical solutions, shape best practices, and deliver results in a fast-paced, supportive environment.</li><li>
Collaboration: Join a cross-functional, high-performing team where your expertise is valued and your contributions make a real difference.</li></ul><p></p><p><b>
About the team</b></p><p>
Our inclusive and global teams win together every day. We&rsquo;re proud to have the best minds in the industry, whom you can learn from as you grow your career. The people, the energy, and the connections are unmatched. Come and be part of an ever-evolving company and get dynamic opportunities that transcend borders.</p><p></p><p><b>
What makes a Globalpayer?</b></p><p>
Globalpayers think like a client, act like an owner, and win as one team. We&rsquo;re curious and innovative &ndash; always finding better ways to deliver impact. We empower each other to make decisions, and our passion drives excellence in everything we set out to do.</p><p></p><p>
Does this sound like you? Then you sound like a Globalpayer. Apply now to take your career global.</p><p></p><p>
#LI-AB1</p></div>

Senior ML Software Engineer

Information Tech Consultants

<div>
 <p>
  <strong>
   Job Title:
  </strong>
  Data Scientist/Machine Learning Engineer
 </p>
 <p>
  <strong>
   Location:
  </strong>
  UK
 </p>
 <p>
  <strong>
   Experience:
  </strong>
  2&ndash;5 years
 </p>
 <p>
  <strong>
   Education:
  </strong>
  Master's in Science (IT/Computer Science/Engineer)
 </p>
 <p>
  <strong>
   Employment Type:
  </strong>
  Full-Time
 </p>
 <p>
  <strong>
   UK based candidates only.
  </strong>
 </p>
 <p>
  Information Tech Consultants Ltd (ITC) is an IT management and consulting firm based in Central London. Information Tech Consultants Ltd (ITC) is an IT management and consulting firm based in Central London. We are responsible for sourcing and hiring field experts for various companies. We primarily work with Software and Cloud Hosted Services organizations as well as Mobile Apps and Service companies.
 </p>
 <p>
  <strong>
   Required Skills:
  </strong>
 </p>
 <ul>
  <li>
   2-4 years of experience in Data science/Machine learning models from coding to deployment.
  </li>
  <li>
   Work with datasets using Python or R, SQL, No SQL.
  </li>
  <li>
   Assist in developing predictive and statistical models
  </li>
  <li>
   Write and optimize queries using SQL.
  </li>
  <li>
   Familiarity with data manipulation libraries (Pandas, NumPy), Understanding of statistics and probability.
  </li>
  <li>
   Hands-on experience with ML libraries like Scikit-learn, TensorFlow, or PyTorch.
  </li>
 </ul>
 <p>
  <strong>
   Preferred Skills:
  </strong>
 </p>
 <ul>
  <li>
   Hands on experience in coding (mandatory python and SQL or C++).
  </li>
  <li>
   Understanding of Generative AI, Computer Vision cloud technology, NLP, Deep Learning.
  </li>
  <li>
   Familiarity working with large data sets.
  </li>
  <li>
   Project Management background preferred.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Qualifications :
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Master&rsquo;s (Required)
   </strong>
   in Data Science, Mathematics, Statistics, Economics, IT related fields and 2- 4 years of experience in Information Technology.
  </li>
  <li>
   You should be entitled to work in the UK with legal work authorization status.
  </li>
  <li>
   Must be willing to travel within the UK as per project/client requirements.
  </li>
  <li>
   Excellent communication skills and teamwork skills.
  </li>
 </ul>
 <p>
 </p>
</div>


Machine Learning Engineer

Ciklum

<p></p><div><div><div><div><div><div><div><div><div><div><div><b>Ciklum</b> is looking for a <b>Expert Agentic AI Engineer</b> to join our team full-time in the UK .<br>
We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.</div><p><b>
About the role:</b></p><p>
As a Expert Agentic AI Engineer, become a part of a cross-functional development team engineering experiences of tomorrow.</p><p><b>
Responsibilities:</b></p><ul><li>
Design, build, train, and deploy production-grade Machine Learning, Deep Learning, or Natural Language Processing (NLP) models</li><li>
Optimize ML models for enterprise-scale latency, throughput, and performance, ensuring flawless integration with data warehouses and automated workflow bots</li><li>
Partner with Data Engineers to engineer high-quality data pipelines, automated feature stores, and secure data preprocessing routines</li><li>
Establish and scale MLOps workflows to handle model lineage tracking, code versioning, automated validation gates, and continuous deployment pipelines</li><li>
Set the core technical direction for AI engineering across squads, evaluate emerging AI methodologies, and provide high-level mentorship to senior team members</li></ul><p><b>
Requirements:</b></p><ul><li>
5+ years (Senior) or 8+ years (Expert) of professional experience developing, shipping, and maintaining machine learning models in live production environments</li><li>
Agentic Frameworks: Hands-on experience building autonomous workflows, custom plugins, and orchestration logic using Microsoft Copilot Studio or semantic kernels</li><li>
Cloud AI Infrastructure: Proven experience deploying and fine-tuning generative AI models, prompt flow, and vector databases within Azure AI Foundry (formerly Azure AI Studio)</li><li>
Tool Integration: Strong background in connecting LLMs to external APIs, enterprise data sources, and robotic process automation (RPA) tools to enable autonomous action execution</li><li>
Elite proficiency in Python paired with extensive experience using core ML libraries and frameworks (such as PyTorch, TensorFlow, Scikit-Learn, or Hugging Face)</li><li>
Hands-on experience working with MLOps tracking tools and cloud-based AI infrastructure ecosystems (such as MLflow, Kubeflow, AWS SageMaker, or Azure ML)</li><li>
Strong computer science fundamentals, including advanced knowledge of data structures, algorithmic complexity, and clean code principles. a formal degree in Computer Science, Data Science, Mathematics, or a highly quantitative field is strongly preferred</li></ul><p><b>
What`s in it for you?</b></p><ul><li>
Strong community: Work alongside top professionals in a friendly, open-door environment</li><li>
Growth focus: Take on large-scale projects with a global impact and expand your expertise</li><li>
Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications</li><li>
Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies</li><li>
Care: Healthcare, Basic Life Insurance, Short and Long-term disability insurance according to the Company&rsquo;s Benefit Plans</li></ul><p><b>
About us:</b></p><p>
At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you&rsquo;ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. In the UK, Ciklum is growing fast&mdash;inviting experienced professionals to lead digital transformation alongside Fortune 500 clients. Be part of a company where innovation and impact go hand in hand.</p><p><b>
Explore, empower, engineer with Ciklum!</b></p><p>
Interested already? We would love to get to know you! Submit your application. We can&rsquo;t wait to see you at Ciklum.</p><p>
#LI-VH1</p></div>
</div></div></div></div></div></div><div></div><div><div><div><div><div><div><p>REQUIRED SKILLS</p>
<div><ul><p>Agentic AI</p>
</ul></div></div></div></div></div></div></div><div></div><div><div><div><div><div><div><div>
</div></div></div></div></div></div></div><div><div><div><div><div><div><p>JOB INFO</p>
<div><div><div><ul><div><div>Job Identification</div>
<div>3619</div>
</div><div><div>Job Category</div>
<div>Intelligent Automation</div>
</div><div><div>Posting Date</div>
<div>07/03/2026, 02:34 AM</div>
</div><div><div>Locations</div>
<div> <div></div><div><div>London
</div></div>(Hybrid)</div></div></ul></div></div></div></div></div></div></div></div></div></div></div></div><p></p>

Expert Agentic AI Engineer

Hyper Recruitment Solutions

<div>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 We are currently looking for a Machine Learning Engineer to join a pioneering research organisation dedicated to advancing drug discovery through innovative approaches to disordered proteins. This is an exciting opportunity for a candidate with a strong industrial background and a passion for applying machine learning to complex biological problems. Based at their modern facility, you will play a key role in driving forward cutting-edge research in a dynamic, open-source environment.
 <br/>
 <br/>
 In this position, you will be responsible for developing and deploying machine learning models specifically tailored to tackle the challenges presented by highly dynamic and disordered proteins, with a particular focus on NMR data. You will work independently within a small, autonomous team, influencing research directions and interpreting self-generated data to uncover new insights in this emerging scientific frontier.
 <br/>
 <br/>
 <strong>
  Key Duties And Responsibilities
  <br/>
  <br/>
 </strong>
 Your duties as the Machine Learning Engineer will be varied, however the key duties and responsibilities are as follows:
 <br/>
 <br/>
 <ul>
  <li>
   Develop and implement machine learning models to analyse complex biological data, particularly focusing on disordered proteins.
  </li>
  <li>
   Collaborate with scientific teams to interpret data, draw insights, and refine experimental approaches based on model findings.
  </li>
  <li>
   Engage directly with real biological problems, balancing modelling expertise with practical, applied research.
  </li>
  <li>
   Use your technical knowledge to drive projects independently within a small, open-source environment, ensuring results are meaningful and impactful.
  </li>
  <li>
   As the Machine Learning Engineer, you will be pivotal in translating scientific challenges into effective computational solutions.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Role Requirements
  <br/>
  <br/>
 </strong>
 To be successful in your application to this exciting role as the Machine Learning Engineer we are looking to identify the following on your profile and past history:
 <br/>
 <br/>
 <ul>
  <li>
   A Degree or higher level in a relevant field (e.g., Computer Science, Data Science, Bioinformatics) with proven applied experience.
  </li>
  <li>
   Demonstrated industrial experience in developing machine learning solutions within biological or biochemical research settings.
  </li>
  <li>
   Strong understanding of disordered proteins, protein dynamics, and limitations of static techniques like NMR.
  </li>
  <li>
   Proven ability to work independently, drive projects forward, and influence research directions within small, autonomous teams.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  WHAT&rsquo;S IN IT FOR YOU?
  <br/>
  <br/>
 </strong>
 This is a rare opportunity to contribute to groundbreaking research in drug discovery at a forward-thinking, non-profit organisation. You will benefit from a collaborative, open-source environment with significant influence over scientific direction, paired with a competitive salary package and the potential for sponsorship if required. Working four days on-site offers excellent work-life balance, within a state-of-the-art facility supported by recent government funding.
 <br/>
 <br/>
 Key Words:
 <em>
  Machine Learning
 </em>
 /
 <em>
  Bioinformatics
 </em>
 /
 <em>
  Disordered Proteins
 </em>
 /
 <em>
  NMR
 </em>
 /
 <em>
  Applied Research
 </em>
 /
 <em>
  Autonomy
 </em>
 /
 <em>
  Biological Data Analysis
 </em>
 /
 <em>
  Open Source
 </em>
 /
 <em>
  Innovation
 </em>
 /
 <em>
  Drug Discovery
  <br/>
  <br/>
 </em>
 "Hyper Recruitment Solutions Ltd (HRS) is an Equal Opportunities employer. We welcome applications from anyone who meets the role requirements. HRS exclusively supports the STEM sectors, combining recruitment expertise with scientific knowledge to help you advance your career".
</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>


Lead Data Scientist

Cushman & Wakefield

<div><p><b>Job Title</b></p>
Junior Analytics Engineer<p><b>
Job Description Summary</b></p><p><b>
Job Description</b></p><p>
As a Junior Analytics Engineer within the EMEA Business Intelligence team, you will be an integral part of the Analytics Engineering pillar, contributing to the development and maintenance of the data foundation that powers BI delivery across EMEA. Working closely with senior Analytics Engineers, you will support the design and build of semantic models, curated datasets, and reusable data assets on our central data platform, gaining hands-on experience with enterprise-scale data modelling and platform engineering in a collaborative, high-performing team. You will work in close collaboration with the BI and Data Science &amp; Engineering teams, helping to lay the groundwork for data assets that increasingly support AI and agentic use cases alongside traditional BI delivery. You will start to develop an understanding of the business context behind the data you work with, helping to translate business needs into well-structured data assets and beginning to build the analytics translation skills that connect data and business outcomes. This is a role for someone who is technically curious, eager to learn, and motivated to build a strong foundation in analytics engineering. You will be guided and supported throughout, with clear opportunities to grow your skills, take on increasing responsibility, and develop toward a more senior role within the pillar.</p><p></p><p><b>
Responsibilities:</b></p><ul><li><p>
Contribute to the design, build, and maintenance of semantic models and curated datasets on our central data platform, working under the guidance of senior Analytics Engineers.</p></li><li><p>
Support the standardisation of datasets, business logic, and data models to enable reusability and consistency across BI teams and markets.</p></li><li><p>
Assist with onboarding market-specific datasets onto our central data platform, collaborating with local stakeholders to understand data sources and requirements.</p></li><li><p>
Work closely with senior team members to ensure data assets meet the requirements of BI products being developed by the BI Development team.</p></li><li><p>
Develop a working understanding of the business context behind data requests, supporting senior team members in translating business needs into data structures and logic.</p></li><li><p>
Collaborate closely with Data Science &amp; Engineering colleagues, building familiarity with how data assets are used and shared across teams.</p></li><li><p>
Contribute to data quality checks and basic performance monitoring of data models and semantic layers, supporting senior team members in identifying improvements.</p></li><li><p>
Support early-stage work on building data foundations that can be used for AI and agentic use cases, such as preparing clean, well-structured datasets ready for future AI applications.</p></li><li><p>
Maintain clear documentation of data models, datasets, and platform assets, ensuring work is well-described and easy for others to understand and build on.</p></li><li><p>
Participate in peer reviews of data models and platform assets, incorporating feedback constructively to develop technical skills and maintain quality standards.</p></li><li><p>
Follow established best practices for data modelling, naming conventions, and platform governance, developing familiarity with the team's standards and ways of working.</p></li><li><p>
Engage actively in training, bootcamps, and mentoring programmes, taking ownership of personal development and building expertise in the tools and technologies used by the team.</p></li><li><p>
Support testing and quality assurance activities across project delivery, helping to ensure data assets and platform changes are reliable before release.</p></li></ul><p></p><p><b>
Requirements:</b></p><ul><li><p>
Bachelor's or Master's degree in Computer Science, Data Engineering, Mathematics, Statistics, or a related technical discipline.</p></li><li><p>
Some practical experience with data engineering, analytics engineering, or BI development through employment, internships, or academic projects.</p></li><li><p>
Foundational understanding of SQL and a willingness to develop proficiency in building and optimising data models.</p></li><li><p>
Basic familiarity with data modelling concepts such as star schema or dimensional modelling; formal experience is an advantage but not required.</p></li><li><p>
Exposure to enterprise data platforms such as Databricks, Microsoft Fabric, Azure Synapse, or Snowflake is desirable.</p></li><li><p>
Awareness of Power BI or other BI tools and an interest in understanding how data assets underpin BI product development.</p></li><li><p>
Curiosity about AI, machine learning, and agentic technologies, and how data platforms are structured to support these use cases.</p></li><li><p>
An interest in understanding business needs and translating them into data and analytics solutions, with a willingness to develop commercial awareness alongside technical skills.</p></li><li><p>
Strong attention to detail and a methodical approach to building, testing, and documenting data assets.</p></li><li><p>
A collaborative and proactive mindset, with the eagerness to learn from senior team members and contribute to a high-performing team.</p></li><li><p>
Good communication skills, with the ability to ask clear questions and document work clearly.</p></li><li><p>
Knowledge of the real estate sector is a plus but not required.</p></li><li><p>
Fluent in English; additional European languages are an advantage.</p></li></ul><p></p><p><br>
Cushman &amp; Wakefield is an equal opportunity / affirmative action employer. All qualified candidates will receive consideration for employment without regard to ethnicity, gender, gender identity or expression, sexual orientation, age, disability, religion, marital status, or any other legally protected characteristic. Cushman &amp; Wakefield is committed to equity in employment, and our goal is to have a diverse, inclusive and barrier-free workplace. If you are a person with a disability and need any other accessible accommodations during the hiring process, you are invited to bring this to the Talent Acquisition Advisor&rsquo;s attention once they have made contact.</p><br>
<p></p>
INCO: &ldquo;Cushman &amp; Wakefield&rdquo;</div>

Junior Analytics Engineer

Bloomberg

<div>
 Location
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 London
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 Business Area
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 Engineering and CTO
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 Ref #
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 10049302
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 <strong>
  Description &amp; Requirements
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  <br/>
 </strong>
 Bloomberg&rsquo;s Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
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 Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions.
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 Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
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 We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications.
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 <br/>
 As a Senior ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed AI development life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.
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  Join the AI Group as a Senior ML Platform Engineer and you will have the opportunity to:
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 </strong>
 <ul>
  <li>
   Architect, build, and diagnose multi-tenant AI platform systems
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   Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring
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  <li>
   Work with AI experts to understand workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms
  </li>
  <li>
   Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience
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  <li>
   Design CI/CD automation frameworks that incorporate regulatory requirements
  </li>
  <li>
   Develop cloud-native deployment patterns for AI systems across environments
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  <li>
   Troubleshoot and debug user issues
  </li>
  <li>
   Provide operational and user-facing documentation
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   <br/>
  </li>
 </ul>
 <strong>
  We are looking for a Senior ML Platform Engineer with:
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 </strong>
 <ul>
  <li>
   Proven years of experience working with an object-oriented programming language (Python, Go, etc.)
  </li>
  <li>
   Experience designing cloud-native, distributed platforms
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  <li>
   Strong knowledge of Kubernetes, Argo, and container orchestration technologies
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   Previous experience with modern CI/CD tools and GitOps workflows
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   Familiarity with implementing automation for model development lifecycles
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  <li>
   A proactive mentality and ability to collaborate with peers, stakeholders, and management
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   A Degree in Computer Science, Engineering, Mathematics, or similar field of study or equivalent work experience
  </li>
  <li>
   An understanding of Computer Science fundamentals such as data structures and algorithms
   <br/>
   <br/>
  </li>
 </ul>
 We give back to the technology community and you can read more about our outreach at:
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 <br/>
 If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
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 Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.
</div>


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