data scientist

senior data scientist

lead software engineer

lead data scientist

lead devops engineer

lead scientist

Data Idols

<div><h2 class="jobSectionHeader">Lead Data Scientist &ndash; Commercial</h2>
<h3 class="jobSectionHeader">&pound;95,000 &ndash; &pound;105,000</h3>
<h3 class="jobSectionHeader">London hybrid</h3>

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.
<h3 class="jobSectionHeader">
The Opportunity</h3>

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.

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.

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.
<h3 class="jobSectionHeader">
Skills and experience</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>
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.
<h3 class="jobSectionHeader">
Lead Data Scientist &ndash; Commercial</h3></div><div></div>

Lead Data Scientist

Hiscox

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

Faculty

<div><h2 class="jobSectionHeader">Why Faculty? 
</h2> 
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we&rsquo;ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.
We don&rsquo;t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we&rsquo;re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology, join a company where you&rsquo;ll be empowered to envision its most powerful applications, and to make them happen.<div> 
</div><h2 class="jobSectionHeader">
About the team</h2><div> 
</div>Our Public Services Business Unit is committed to leveraging AI for the benefit of individual citizens and the public good. 
 
From our work informing strategic government decisions, to optimising our NHS, through to reducing bureaucratic backlogs - we know that AI offers opportunities to drive improvements at every level of Government and we are proud to lead on some of the most impactful work happening in the sector. 
 
Because of the nature of the work we do with our Government clients, you may need to be eligible for UK Security Clearance (SC) and willing to work on site with these clients from time to time.<h2 class="jobSectionHeader">
About the role</h2><div></div> 
As a Lead Data Scientist, you'll take on a pivotal, entrepreneurial role, functioning as the technical expert who thrives on complexity and commercial impact. You will be responsible for setting the technical direction and ensuring the high-quality, scalable delivery of our most challenging, high-impact projects. 
 
 
 
This position combines deep expertise in machine learning with strategic oversight to define project roadmaps, manage technical risk, and architect reliable solutions. Your focus will be on driving innovation, mentoring cross-functional teams, and actively shaping both our technical standards and long-term customer relationships.<div></div><h2 class="jobSectionHeader"> 

What you'll be doing:</h2><div></div><ul><li> 
Setting the technical direction for complex, business-critical projects and expertly balancing trade-offs between speed, innovation, and reliability.</li><li>
Designing and implementing reliable, production-grade technical solutions, ensuring comprehensive documentation of architectures and specifications.</li><li>
Defining project problems, developing clear roadmaps, and overseeing end-to-end delivery across multi-disciplinary workstreams.</li><li>
Leading technical scoping and feasibility studies for high-value sales opportunities and strategic customer engagements.</li><li>
Managing relationships and communications with demanding clients, fostering trust and aligning technical solutions with shared long-term commercial goals.</li><li>
Driving the adoption of best practices, shared resources, and robust technical processes across the wider Data Science craft.</li><li>
Mentoring and developing other data scientists and team members, actively contributing to the growth and technical excellence of the organisation.</li></ul><div> 
</div><h2 class="jobSectionHeader">
Who we're looking for:</h2><div></div><ul><li> 
You bring depth of expertise in at least one machine learning domain and strong technical breadth across the entire data science landscape.</li><li>
You are a skilled technical leader, proficient in mentoring individuals, managing teams (including other managers), and rolling out impactful tools and workflows.</li><li>
You have proven project management expertise, capable of dividing complex, ill-defined problems into actionable, clearly defined workstreams with timelines you can defend.</li><li>
You are adept at managing ill-defined, high-risk tasks, consistently delivering innovative and practical outcomes under commercial pressure.</li><li>
You possess strong customer leadership skills, able to act as a trusted technical advisor and drive long-term strategic relationships with demanding clients.</li><li>
You excel at cross-functional collaboration, effectively aligning technical strategy with Engineering, Commercial (BD), and Infrastructure teams.</li><li>
You have experience extending technical oversight to business unit-level initiatives, using your vision to influence and contribute to organisational success.</li></ul><div> 
</div><h2 class="jobSectionHeader">
Our Interview Process</h2><div></div><ul><li> 
Talent Team Screen (30 minutes)</li><li>
Introduction to the team (45 minutes)</li><li>
Technical Interview (90 minutes)
</li><li>Commercial Interview (60 minutes)</li></ul>
#LI-PRIO<h2 class="jobSectionHeader">
Our Recruitment Ethos</h2>
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We&rsquo;re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Some of our standout benefits:<ul><li>
Unlimited Annual Leave Policy</li><li>
Private healthcare and dental</li><li>
Enhanced parental leave</li><li>
Family-Friendly Flexibility &amp; Flexible working</li><li>
Sanctus Coaching</li><li>
Hybrid Working</li></ul>
If you don&rsquo;t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.</div>

Greyparrot

<div>
 
 About The Role
 
 
 
 The world is in a waste crisis. Currently we produce 2.1 billion tons of solid waste per year. Data collection of the waste we produce is non-existent, meaning no systematic transparency and no accountability. It means that recycling targets are not upheld, dumping of waste into our oceans remains nobody&rsquo;s responsibility, recyclables get sent to landfill or incineration, and producers have little visibility of how their packaging performs at end of life. Recycling rates remain at 10% and, unless we change, by 2040 the plastic stock in the ocean will have quadrupled - a problem that already costs society $1.5 trillion each year.
 
 
 Our mission is to increase transparency and automation in waste management to accelerate the circular economy. Greyparrot's camera and AI systems generate granular, real-time waste composition data across facilities worldwide. That data is only valuable if it can be turned into insight that clients trust and act on.
 
 
 We are looking for a Lead Data Scientist to act as the &ldquo;engine room&rdquo; of our data methodology, transforming raw computer vision outputs into insights the industry can rely on.
 
 
 The near-term priority is delivery; owning the contracted Deepnest client analytics, the reports and data clients have paid for, shipped on time and to a high standard. The metric engine work is what makes delivery scalable and trusted; developing the statistical methodology that turns raw computer vision outputs into defensible, quantified waste metrics. Both matter from day one.
 
 
 Longer term will support other customer &amp; marketing facing work as well.
 
 
 You will report directly to the CTO and have one direct report, Data Analyst, with scope to grow as the business scales. You will sit alongside the Head of Data R&amp;D who owns longer-term structural research upstream of the metric engine.
 
 
 The data is physical-world data: noisy, incomplete, and derived from computer vision models running in live recycling facilities. This is not a clean-warehouse role. It suits someone who treats messy data as the problem to solve, not a reason to wait.
 
 
 This role will ideally be based in our London office at least one day a week, and reports to our CTO.
 
 
 
 Outcomes
 
 
 
 These are the results you will be held to. How you achieve them is yours to figure out.
 
 
 <ul>
 <li>
 The metric engine advances The next iteration of Greyparrot's statistical modelling framework is implemented; strengthening how we reconcile process flows, extrapolate across coverage gaps, and quantify confidence in outputs. At 12 months, a credible path toward a confidence-aware, probabilistic foundation is underway. The methodology is documented, defensible, and ready to be productionised by ML Ops.
 </li>
 <li>
 Contracted deliverables ship on time, every time Deepnest clients receive their analytical reports and insight outputs to a consistently high standard and on schedule. The methodology behind the numbers is defensible, the findings are actionable, and clients trust what they receive. There are no surprises at delivery.
 </li>
 <li>
 Insight delivery is repeatable, not heroic A documented framework - templates, quality standards, methodology - exists so output quality does not depend on starting from scratch each engagement. The process is written down, transferable, and does not live in your head.
 </li>
 <li>
 R&amp;D and delivery are in sync The Head of Data, R&amp;D has a clear, consistent picture of which model outputs translate to client value. You provide that feedback loop reliably, and it shapes what gets prioritised on the research roadmap. There is no gap between what the models produce and what clients actually need.
 
 
 
 </li>
 </ul>
 
 Experience &amp; Background
 
 
 
 <ul>
 <li>
 Physical-world data: 5+ years in data science working with large-scale, noisy real-world data - environments where data quality and fail modes are constant challenges.
 </li>
 <li>
 Background in high-volume, complex real-world data industries: satellite and geospatial, weather forecasting, industrial IoT, manufacturing, is a bonus.
 </li>
 <li>
 Deep learning familiarity: A strong practical understanding of the implications of working with data derived from deep learning models; specifically the nuances of integrating computer vision outputs into broader statistical simulations. You know where the model can mislead you and how to account for it.
 </li>
 <li>
 Python and SQL: You build analysis pipelines and get to robust outputs independently, without needing a data engineering team to do it for you. This is not an expectation of production ready output.
 </li>
 <li>
 Owned external deliverables: Reports or data products that clients or senior stakeholders have relied on. You understand what makes insight land versus what gets ignored.
 </li>
 <li>
 Built from scratch: You have built methodology and process where none existed, not just inherited and executed. You are comfortable setting standards and navigating ambiguity at pace.
 </li>
 <li>
 People leadership: You have managed or mentored at least one person and have a clear view of what good looks like. You can set a standard and give others the structure to work within it.
 
 
 
 </li>
 </ul>
 
 What Success Looks Like
 
 
 
 
 90 days:
 
 You have owned at least one contracted Deepnest deliverable end-to-end. Your team has clear scope and is working effectively. You have a clear picture of the current methodology, where the metric engine stands, and where the gaps are.
 
 
 
 6 months:
 
 The next iteration of the proprietary metric engine and data modelling framework is implemented. A repeatable delivery process is in place and documented.
 
 
 ________________________________________________________________
 
 
 
 About Greyparrot
 
 
 
 The world is in a waste crisis. Currently we produce 2.1 billion tons of solid waste per year. Data collection of the waste we produce is non-existent, meaning no systematic transparency and no accountability. It means that recycling targets are not upheld, dumping of waste into our oceans remains nobody's responsibility, recyclables get sent to landfill or incineration, and producers get away with sub-standard packaging. Thus, recycling rates stubbornly remain at 10% and, unless we change, by 2040 the plastic stock in the ocean will have quadrupled - a problem that already costs society $1.5 trillion each year.
 
 
 Our mission is to digital waste flows to accelerate the circular economy. Currently, our camera system and AI software are deployed in recycling plants and waste facilities around the world to measure material flows and provide waste analytics. We have compiled a team of experts to deploy our technology and we&rsquo;re looking to expand our team.
</div>

Talan

<div>Company Description 
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). 
Job Description 
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.
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.
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.
Required skills &amp; experience:<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> 

Qualifications 
To qualify for this role, you must have:
<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>
Ideally, you&rsquo;ll also have, but not essential:<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>
You must be:<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>
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<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>
Why join:
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.</div>

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

Wise

<div>Company Description 
Wise is a global technology company, building the best way to move and manage the world&rsquo;s money. 
Min fees. Max ease. Full speed.
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.
As part of our team, you will be helping us create an entirely new network for the world's money. 
For everyone, everywhere.
More about our mission and what we offer. 
Job Description 
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.
Your work will have a direct impact on Wise&rsquo;s mission and millions of our customers. 
About the Role:
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.
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:
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.
What you&rsquo;ll own<ul><li>
Python microservices that run quantitative models in production</li><li>
Monitoring, alerting, and reliability for real-time pricing and risk systems</li><li>
Shared quant libraries used across multiple services</li><li>
CI/CD pipelines, deployment and operational excellence</li><li>
Incident response and root cause analysis for production issues</li></ul>
Where you&rsquo;ll grow<ul><li>
Real-time curve construction (yield curves, FX forwards, vol surfaces)</li><li>
Pricing models for new instruments and products</li><li>
Trading strategy development and optimisation</li><li>
Risk modelling alongside the Risk team (VaR, stress testing, scenario analysis)</li><li>
Backtesting frameworks and model validation</li><li>
Customer behaviour modelling, pricing strategy and product launch support</li><li>
Collaborating with product teams to translate quantitative insights into customer-facing decisions</li></ul> 
Qualifications 
What we&rsquo;re looking for<ul><li>
4+ years building and maintaining production Python systems</li><li>
Strong experience with microservices, databases, and production infrastructure</li><li>
Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.)</li><li>
Quantitative background - maths, physics, engineering or finance - you can read a model and reason about correctness</li><li>
Experience with testing, monitoring, and debugging complex systems under load</li><li>
A product mindset - you think about who uses your systems and why</li><li>
Clear communicator who can work cross-functionally with other quants, analysts, traders, product managers and engineers</li></ul>
It&rsquo;s a bonus if you are familiar with<ul><li>
FX or financial markets experience</li><li>
Term structure modelling, stochastic calculus or Monte Carlo methods</li><li>
Interest rate curve bootstrapping</li><li>
Algorithmic execution experience</li><li>
Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.)</li></ul>
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.
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.
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 
Additional Information<div></div> 
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.
We're proud to have a truly international team, and we celebrate our differences. 
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.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.</div>

Lead Data Scientist (Quant) - Treasury FX

Wise Australia Investments

<div><div><div>Wise is a global technology company, building the best way to move and manage the world&rsquo;s money. 
Min fees. Max ease. Full speed.
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.
As part of our team, you will be helping us create an entirely new network for the world's money. 
For everyone, everywhere.
. 
Job Description 
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.
Your work will have a direct impact on Wise&rsquo;s mission and millions of our customers. 
About the Role:
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.
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:
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.
What you&rsquo;ll own<ul><li>
Python microservices that run quantitative models in production</li><li>
Monitoring, alerting, and reliability for real-time pricing and risk systems</li><li>
Shared quant libraries used across multiple services</li><li>
CI/CD pipelines, deployment and operational excellence</li><li>
Incident response and root cause analysis for production issues</li></ul>
Where you&rsquo;ll grow<ul><li>
Real-time curve construction (yield curves, FX forwards, vol surfaces)</li><li>
Pricing models for new instruments and products</li><li>
Trading strategy development and optimisation</li><li>
Risk modelling alongside the Risk team (VaR, stress testing, scenario analysis)</li><li>
Backtesting frameworks and model validation</li><li>
Customer behaviour modelling, pricing strategy and product launch support</li><li>
Collaborating with product teams to translate quantitative insights into customer-facing decisions</li></ul> 
Qualifications 
What we&rsquo;re looking for<ul><li>
4+ years building and maintaining production Python systems</li><li>
Strong experience with microservices, databases, and production infrastructure</li><li>
Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.)</li><li>
Quantitative background - maths, physics, engineering or finance - you can read a model and reason about correctness</li><li>
Experience with testing, monitoring, and debugging complex systems under load</li><li>
A product mindset - you think about who uses your systems and why</li><li>
Clear communicator who can work cross-functionally with other quants, analysts, traders, product managers and engineers</li></ul>
It&rsquo;s a bonus if you are familiar with<ul><li>
FX or financial markets experience</li><li>
Term structure modelling, stochastic calculus or Monte Carlo methods</li><li>
Interest rate curve bootstrapping</li><li>
Algorithmic execution experience</li><li>
Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.)</li></ul>
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.
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.
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 
Additional Information<div></div> 
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.
We're proud to have a truly international team, and we celebrate our differences. 
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.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on </div></div><div><div><div><div>Instagram</div></div></div></div></div><div></div>

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Lead Data Scientist (Quant) - Treasury FX

Lead Data Scientist (Quant) - Treasury FX