data engineer

data scientist

senior data scientist

senior data engineer

analytics engineer

data science analyst

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

Talan

<div><b>Company Description</b><p><br>
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI).</p><b><br>
Job Description</b><p><br>
As our AI practice grows, we are looking for a capable, hands-on AI Engineer to help build and deliver the solutions at the heart of our client work. Coming from a data science background, you are equally comfortable applying proven machine-learning techniques to traditional analytics problems and working with the latest generative AI (large language models, retrieval-augmented generation, and agent-based applications). You enjoy building, you write dependable code, and you turn well-defined designs into working software.</p><p>
This is a delivery-focused role that sits a level below our Lead Data Scientists. You will own meaningful workstreams within a project rather than the whole engagement, working to an architecture and plan shaped by more senior colleagues. In return, you will gain breadth across modern AI, exposure to real client problems,</p><p>
You will also be a supportive presence within the team, helping your peers solve problems, sharing what you learn, and giving day-to-day guidance to graduate and junior resources working alongside you.</p><p><b>
Required skills &amp; experience:</b></p><ul><li>
Build, test, and deploy AI and machine learning components within client projects to the standards and designs set by senior colleagues.</li><li>
Develop GenAI and LLM-based features (prompting, retrieval-augmented generation, and simple agentic workflows) alongside more traditional ML models.</li><li>
Deliver classical data science tasks (data preparation, feature engineering, model training, and evaluation) on projects that call for them.</li><li>
Translate solution designs into clean, well-documented, production-minded code.</li><li>
Contribute to model evaluation, testing, and monitoring.</li><li>
Support and guide very junior and graduate resources, reviewing their work and helping them grow.</li><li>
Help peers unblock technical problems and share knowledge across the team.</li><li>
Take part in client and team discussions and communicate your work clearly.</li></ul><br>
<b>
Qualifications</b><p><b><br>
To qualify for this role, you must have:
</b></p><ul><li>Typically, 2&ndash;4 years' experience in data science, machine learning, or AI engineering.</li><li>
Solid grounding in core data science and machine learning.</li><li>
Practical experience with LLMs and generative AI, including prompting and RAG.</li><li>
Familiarity with how AI agents are built and orchestrated.</li><li>
Strong Python and common data/ML libraries; good engineering habits.</li><li>
Clear communicator and collaborative team player.</li></ul><p><b>
Ideally, you&rsquo;ll also have, but not essential:</b></p><ul><li>
Exposure to cloud AI platforms, Azure a plus.</li><li>
Experience practicing MLOps and LLMOps.</li><li>
Early experience mentoring junior colleagues.</li><li>
Interest in consulting and client-facing delivery.</li></ul><p><b>
You must be:</b></p><ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul><p>
#TalanUK #LI-HB1</p><b><br>
Additional Information</b><p><b><br>
Compensation &amp; Benefits Package:</b></p><ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul><p><b>
Why join:</b></p><p>
This is a role built for momentum, working across the full spectrum of modern AI, learning from senior architects and leads on real engagements, with genuine responsibility from day one and a clear path into a leadership track.</p></div>

AI Engineer (LLMs, Agents & Applied Data Science)

<div><b>Company Description</b><p><br>
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI).</p><b><br>
Job Description</b><p><br>
We are hiring a Lead Data Scientist to drive the technical delivery of our most demanding AI engagements and to lead a growing team of data scientists and AI engineers. This role is for a practitioner who is equally fluent in the rigour of traditional data science (statistical modelling, machine learning, experimentation) and the fast-moving world of large language models and agentic AI. You understand that the best solutions often combine both.</p><p>
You will own delivery from problem framing through to deployment, ensuring the work is technically sound, commercially valuable, and aligned to the architectural vision. As a lead, you will mentor the team, raise engineering and modelling standards, and act as a trusted technical partner in client conversations. You will help clients see not just what is possible, but what is practical and worth doing.</p><p>
This is a delivery-focused leadership role with genuine breadth: one week you might be tuning a forecasting model, the next designing an agentic workflow or evaluating an LLM pipeline for a client pilot.</p><p><b>
Required skills &amp; experience:</b></p><ul><li>
Lead end-to-end delivery of data science and AI projects, owning technical quality and outcomes.</li><li>
Combine classical ML (regression, classification, forecasting, optimisation) with modern GenAI, LLM, and agent-based approaches as the problem demands.</li><li>
Mentor and develop data scientists, AI engineers, and junior consultants, growing the team's capability.</li><li>
Translate business problems into well-scoped analytical and AI solutions and communicate results to non-technical stakeholders.</li><li>
Ensure best practice across the AI lifecycle &mdash; experimentation, evaluation, testing, deployment, and monitoring.</li><li>
Act as the bridge between architecture and delivery, ensuring implementation stays faithful to design.</li><li>
Support pre-sales and client discussions with credible technical input and realistic estimation.</li><li>
Champion reproducibility, model governance, and responsible practice in everyday delivery.</li></ul><br>
<b>
Qualifications</b><p><b><br>
To qualify for this role, you must have:
</b></p><ul><li>Minimum 5 years in data science or AI delivery, including hands-on leadership of technical teams or workstreams.</li><li>
Strong foundations in machine learning and statistics, with demonstrable production experience.</li><li>
Practical experience with LLMs and generative AI &mdash; prompting, RAG, fine-tuning, and evaluation.</li><li>
Exposure to AI agents and orchestration frameworks, and an appetite to deepen it.</li><li>
Proficiency in Python and the modern data / ML stack; sound data engineering instincts.</li><li>
Excellent communication and stakeholder skills, ideally in client-facing or consulting settings.</li></ul><p><b>
Ideally, you&rsquo;ll also have, but not essential:</b></p><ul><li>
Familiarity with the Azure AI ecosystem (Azure ML, Azure OpenAI, Databricks / Fabric).</li><li>
Experience supporting business development or pre-sales.</li><li>
Domain depth in a regulated or data-rich industry.</li><li>
Contributions to open source, publications, or a visible professional profile.</li></ul><p><b>
You must be:</b></p><ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul><p>
#TalanUK #LI-HB1</p><b><br>
Additional Information</b><p><b><br>
Compensation &amp; Benefits Package:</b></p><ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul><p><b>
Why join:</b></p><p>
You will lead substantive, end-to-end AI work in a practice that is scaling fast and backing its people to grow with it. You will shape how a team works, influence how clients adopt AI, and keep your own skills at the frontier, bridging proven data science with the most current GenAI and agentic techniques. It is an opportunity to lead, deliver, and keep building.</p></div>

Lead Data Scientist (Classical ML, LLMs & AI Agents)

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

HOMETRACK

<div><p>Hometrack is redefining the mortgage journey for lenders, brokers, and consumers by delivering market-leading valuation and property data services to the financial, property, and technology industries. Our key commercial and go-to-market segment is in financial services, primarily mortgage lenders, including nine of the top 10 mortgage providers.</p><p>
At Hometrack, we are looking for an experienced Senior Machine Learning Engineer, to translate POC model code from data science and analytics into robust pipelines and live APIs.</p><p></p><p>
Responsibilities:</p><ul><li>
Oversee the deployment of machine learning models into production, ensuring they perform well in real-world conditions and monitoring their performance over time.</li><li>
Work closely with data scientists, software engineers, product managers, and stakeholders to integrate machine learning solutions into our products and services.</li><li>
Develop automated workflows for model retraining, testing, and deployment to streamline the machine learning lifecycle.</li><li>
Advocate for and implement best practices in software engineering, including code reviews, continuous integration, and continuous delivery (CI/CD) for machine learning models.</li></ul><p></p><p>
Requirements:</p><ul><li>
Strong understanding of machine learning applications, development life cycle processes and tools: CI/CD, version control, testing frameworks, MLOps.</li><li>
Strong Python experience and knowledge, with the ability to write stable, scalable and maintainable code.</li><li>
Experience with data science Python libraries such as Sckit-learn, Pandas, NumPy, PyTorch, PySpark, LightGBM.</li><li>
Have worked with a cloud service, such as AWS.</li><li>
Familiarity developing Infrastructure as code (e.g Terraform, cloudformation).</li><li>
Have some experience with data engineering, building data pipelines with PySpark, SQL (E.g in Databricks, Glue) to power machine learning applications.</li><li>
Comfortable working with Docker and containerised applications.</li><li>
Experience leveraging AI native engineering tooling.</li><li>
Passion for building products that meet customer needs and business objectives.</li><li>
Strong sense of responsibility and a track record of delivering high-quality results in a fast-paced environment.</li></ul><br>
<b>
Benefits</b><br>
<ul><li>
Everyday Flex - greater flexibility over where and when you work</li><li>
25 days annual leave + extra days for years of service</li><li>
Day off for your birthday, house move, good deed day, and digital detox day</li><li>
Cycle to work and electric car schemes
</li><li>Free Calm App membership
</li><li>Enhanced Paternity Leave
</li><li>Fertility Treatment Financial Support
</li><li>Group Income Protection and private medical insurance</li><li>
Gym on-site in London &ndash; or membership in regional offices</li><li>
7.5% pension contribution by the company</li><li>
Discretionary annual bonus up to 10% of base salary</li><li>
Talent referral bonus up to &pound;5K</li></ul></div>

Senior Machine Learning Engineer

Wise Australia Investments

<p></p><div><div><div><p>Wise is a global technology company, building the best way to move and manage the world&rsquo;s money.<br>
<b>Min fees. Max ease. Full speed.</b></p><p>
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.</p><p>
As part of our team, you will be helping us create an entirely new network for the world's money.<br>
<b>For everyone, everywhere.</b></p><p>
.</p><p><b><br>
Job Description</b></p><p><b><br>
We are seeking a talented quantitative developer to join our Treasury Markets Data Science team. This role focuses on owning and operating the production infrastructure behind our FX pricing, risk, and trading systems with the opportunity to broaden the scope of work into traditional quant aspects.</b></p><p><b>
Your work will have a direct impact on </b><b>Wise&rsquo;s mission</b><b> and millions of our customers.</b><br>
</p><p><b>About the Role:</b></p><p>
You'll join the Treasury Markets Data Science team, owning the quantitative infrastructure that powers how Wise manages FX risk across a USD 250bn+ in annual FX volume- serving everyone from retail customers sending money abroad to tier-1 banks via Wise Platform.</p><p>
The wider Treasury FX team includes quants, traders, analysts, product managers and engineers working together to price, hedge, manage and scale FX operations within Wise in real time. Within that, the Data Science team owns the quantitative platform:</p><p>
We run a Python-first, production-grade quant platform: real-time curve construction, multi-instrument pricing, risk analytics, and trading strategy - all built and operated by the same team. Your primary focus is keeping these systems reliable, performant and well-engineered - while thinking deeply about how they serve customers and products. You'll also contribute to the quantitative models themselves as you grow into the domain.</p><p><b>
What you&rsquo;ll own</b></p><ul><li><p>
Python microservices that run quantitative models in production</p></li><li><p>
Monitoring, alerting, and reliability for real-time pricing and risk systems</p></li><li><p>
Shared quant libraries used across multiple services</p></li><li><p>
CI/CD pipelines, deployment and operational excellence</p></li><li><p>
Incident response and root cause analysis for production issues</p></li></ul><p><b>
Where you&rsquo;ll grow</b></p><ul><li><p>
Real-time curve construction (yield curves, FX forwards, vol surfaces)</p></li><li><p>
Pricing models for new instruments and products</p></li><li><p>
Trading strategy development and optimisation</p></li><li><p>
Risk modelling alongside the Risk team (VaR, stress testing, scenario analysis)</p></li><li><p>
Backtesting frameworks and model validation</p></li><li><p>
Customer behaviour modelling, pricing strategy and product launch support</p></li><li><p>
Collaborating with product teams to translate quantitative insights into customer-facing decisions</p></li></ul><p><b><br>
Qualifications</b></p><p></p><p><b><br>
What we&rsquo;re looking for</b></p><ul><li><p>
4+ years building and maintaining production Python systems</p></li><li><p>
Strong experience with microservices, databases, and production infrastructure</p></li><li><p>
Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.)</p></li><li><p>
Quantitative background - maths, physics, engineering or finance - you can read a model and reason about correctness</p></li><li><p>
Experience with testing, monitoring, and debugging complex systems under load</p></li><li><p>
A product mindset - you think about who uses your systems and why</p></li><li><p>
Clear communicator who can work cross-functionally with other quants, analysts, traders, product managers and engineers</p></li></ul><p><b>
It&rsquo;s a bonus if you are familiar with</b></p><ul><li><p>
FX or financial markets experience</p></li><li><p>
Term structure modelling, stochastic calculus or Monte Carlo methods</p></li><li><p>
Interest rate curve bootstrapping</p></li><li><p>
Algorithmic execution experience</p></li><li><p>
Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.)</p></li></ul><p><b>
We&rsquo;re people without borders &mdash; without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you&rsquo;re passionate about learning new things and keen to join our mission, you&rsquo;ll fit right in.</b></p><p><b>
Also, qualifications aren&rsquo;t that important to us. If you&rsquo;ve got great experience, and you&rsquo;re great at articulating your thinking, we&rsquo;d like to hear from you.</b></p><p><b>
And because we believe that diverse teams build better products, we&rsquo;d especially love to hear from you if you&rsquo;re from an under-represented demographic</b></p><p><b><br>
Additional Information</b></p><div></div><p><br>
For everyone, everywhere. We're people building money without borders &mdash; without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.</p><p>
We're proud to have a truly international team, and we celebrate our differences.<br>
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.</p><p>
If you want to find out more about what it's like to work at Wise visit <b>Wise.Jobs</b>.</p><p>
Keep up to date with life at Wise by following us on </p></div></div><p></p><div><div><div><div><b>Instagram</b></div></div></div></div></div><div></div>

Lead Data Scientist (Quant) - Treasury FX

Wise

<div><b>Company Description</b><p><br>
Wise is a global technology company, building the best way to move and manage the world&rsquo;s money.<br>
<b>Min fees. Max ease. Full speed.</b></p><p>
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.</p><p>
As part of our team, you will be helping us create an entirely new network for the world's money.<br>
<b>For everyone, everywhere.</b></p><p>
More about <b>our mission</b> and <b>what we offer</b>.</p><b><br>
Job Description</b><p><b><br>
We are seeking a talented quantitative developer to join our Treasury Markets Data Science team. This role focuses on owning and operating the production infrastructure behind our FX pricing, risk, and trading systems with the opportunity to broaden the scope of work into traditional quant aspects.</b></p><p><b>
Your work will have a direct impact on </b><b>Wise&rsquo;s mission</b><b> and millions of our customers.</b><br>
</p><p><b>About the Role:</b></p><p>
You'll join the Treasury Markets Data Science team, owning the quantitative infrastructure that powers how Wise manages FX risk across a USD 250bn+ in annual FX volume- serving everyone from retail customers sending money abroad to tier-1 banks via Wise Platform.</p><p>
The wider Treasury FX team includes quants, traders, analysts, product managers and engineers working together to price, hedge, manage and scale FX operations within Wise in real time. Within that, the Data Science team owns the quantitative platform:</p><p>
We run a Python-first, production-grade quant platform: real-time curve construction, multi-instrument pricing, risk analytics, and trading strategy - all built and operated by the same team. Your primary focus is keeping these systems reliable, performant and well-engineered - while thinking deeply about how they serve customers and products. You'll also contribute to the quantitative models themselves as you grow into the domain.</p><p><b>
What you&rsquo;ll own</b></p><ul><li><p>
Python microservices that run quantitative models in production</p></li><li><p>
Monitoring, alerting, and reliability for real-time pricing and risk systems</p></li><li><p>
Shared quant libraries used across multiple services</p></li><li><p>
CI/CD pipelines, deployment and operational excellence</p></li><li><p>
Incident response and root cause analysis for production issues</p></li></ul><p><b>
Where you&rsquo;ll grow</b></p><ul><li><p>
Real-time curve construction (yield curves, FX forwards, vol surfaces)</p></li><li><p>
Pricing models for new instruments and products</p></li><li><p>
Trading strategy development and optimisation</p></li><li><p>
Risk modelling alongside the Risk team (VaR, stress testing, scenario analysis)</p></li><li><p>
Backtesting frameworks and model validation</p></li><li><p>
Customer behaviour modelling, pricing strategy and product launch support</p></li><li><p>
Collaborating with product teams to translate quantitative insights into customer-facing decisions</p></li></ul><b><br>
Qualifications</b><p></p><p><b><br>
What we&rsquo;re looking for</b></p><ul><li><p>
4+ years building and maintaining production Python systems</p></li><li><p>
Strong experience with microservices, databases, and production infrastructure</p></li><li><p>
Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.)</p></li><li><p>
Quantitative background - maths, physics, engineering or finance - you can read a model and reason about correctness</p></li><li><p>
Experience with testing, monitoring, and debugging complex systems under load</p></li><li><p>
A product mindset - you think about who uses your systems and why</p></li><li><p>
Clear communicator who can work cross-functionally with other quants, analysts, traders, product managers and engineers</p></li></ul><p><b>
It&rsquo;s a bonus if you are familiar with</b></p><ul><li><p>
FX or financial markets experience</p></li><li><p>
Term structure modelling, stochastic calculus or Monte Carlo methods</p></li><li><p>
Interest rate curve bootstrapping</p></li><li><p>
Algorithmic execution experience</p></li><li><p>
Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.)</p></li></ul><p><b>
We&rsquo;re people without borders &mdash; without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you&rsquo;re passionate about learning new things and keen to join our mission, you&rsquo;ll fit right in.</b></p><p><b>
Also, qualifications aren&rsquo;t that important to us. If you&rsquo;ve got great experience, and you&rsquo;re great at articulating your thinking, we&rsquo;d like to hear from you.</b></p><p><b>
And because we believe that diverse teams build better products, we&rsquo;d especially love to hear from you if you&rsquo;re from an under-represented demographic</b></p><b><br>
Additional Information</b><div></div><p><br>
For everyone, everywhere. We're people building money without borders &mdash; without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.</p><p>
We're proud to have a truly international team, and we celebrate our differences.<br>
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.</p><p>
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.</p><p>
Keep up to date with life at Wise by following us on LinkedIn and Instagram.</p></div>

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Lead Data Scientist (Quant) - Treasury FX

Lead Data Scientist (Quant) - Treasury FX