data engineer

machine learning engineer

senior software engineer

senior data scientist

senior data engineer

senior analytics engineer

HOMETRACK

<div>Hybrid working pattern - 2 days per week from London Bridge Office
Hometrack is seeking an experienced Senior Data Engineer to join our product team to help us deliver Hometrack's Data Services ambitions. By building the best property data sets available, which back the market leading AVM, trusted by 17 out of the top 20 mortgage lenders in the UK, we open the door to helping all our customers make the decisions that matter to them - to buy, to lend, to build.
The Data Services team works with 100s of customers across the property sector ranging from mortgage lenders, house builders, investors, fin &amp; proptech, insurers, telco, retail and utilities, as well as others involved in the housing market. Our mission is to inform decision makers by putting the UK&rsquo;s most trusted property data and insights at the heart of the property ecosystem.
Our market intelligence and customer acquisition, retention and engagement solutions are relied upon by leading industry professionals.
Data Services has a diverse product range covering market, property and mover intelligence, delivered through varying mechanisms including data platforms, reports and APIs, providing maximum flexibility when matching our customers&rsquo; needs to the most effective data solution.
Hometrack is looking for an experienced senior data engineer to help us make this a reality.
What we&rsquo;re looking for in a Senior Data Engineer:<ul><li>
Be accountable for team outcomes, playing your part in achieving team goals and ensuring your contribution positively impacts overall success</li><li>
Be a continual improver, looking for ways to help the team do better and be better, again and again</li><li>
Write maintainable, testable code and enjoy providing code reviews</li><li>
Be experienced with Databricks, Delta Lake and Lakehouse architecture for efficient data management; experience with ETL processes and optimizing data pipelines for performance</li><li>
Be strong in Python, SQL, and PySpark</li><li>
Be passionate about building data products for stakeholders and customers, ensuring they are stable, scalable, secure, accurate, observable, and performant</li><li>
Enjoy collaborating closely with colleagues in Product, Analytics, Security, and Software, explaining technical concepts to non-technical audiences</li></ul></div>

Senior Data Engineer

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 
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.
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,
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.
Required skills &amp; experience:<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> 

Qualifications 
To qualify for this role, you must have:
<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>
Ideally, you&rsquo;ll also have, but not essential:<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>
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:
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.</div>

AI Engineer (LLMs, Agents & Applied Data Science)

Commerce

<div><h1 class="jobSectionHeader">Welcome to the Agentic Commerce Era
</h1>At Commerce, our mission is to empower businesses to innovate, grow, and thrive with our open, AI-driven commerce ecosystem. As the parent company of BigCommerce , Feedonomics , and Makeswift , we connect the tools and systems that power growth, enabling businesses to unlock the full potential of their data, deliver seamless and personalized experiences across every channel, and adapt swiftly to an ever-changing market. We believe in harnessing AI responsibly to unlock new possibilities, and we&rsquo;re looking for individuals who use it intentionally to solve problems, accelerate outcomes, and expand what&rsquo;s possible in their role. Our purpose is to help businesses confidently solve complex commerce challenges so they can build smarter, adapt faster, and grow on their own terms. If you want to be part of a team of bold builders, sharp thinkers, and technical trailblazers who shape the future of commerce, this is the place for you.
<h1 class="jobSectionHeader">Senior Software Engineer - Data Team
</h1>Location: London / UK (Hybrid)
Company: Commerce 
 
<h2 class="jobSectionHeader">About Commerce
</h2>Commerce is an open SaaS ecommerce platform that helps merchants build, run, and grow their businesses.
The Data Team builds systems that support merchant-facing products, integrations, analytics, reporting, and the infrastructure behind them. 
 
<h2 class="jobSectionHeader">About The Role
</h2>We are looking for a Senior Software Engineer who can own complex problems from discovery through production.
This role is not narrowly frontend, backend, or data engineering. The right person can work across services, APIs, event flows, product experience, production debugging, and cross-team delivery.
They should be comfortable taking an unclear business or customer problem, breaking it down, making trade-offs clear, and shipping a reliable solution.
We need someone who raises the engineering bar without needing a lot of direction. 
 
<h2 class="jobSectionHeader">What You Will Do
</h2><ul><li>Design and build reliable services, APIs, and product-facing workflows.
</li><li>Work across backend systems, UI surfaces, event processing, and third-party integrations.
</li><li>Turn unclear problems into concrete technical plans.
</li><li>Own production behavior, including monitoring, alerting, logging, debugging, and runbooks.
</li><li>Work with product, design, infrastructure, support, and other engineering teams.
</li><li>Improve quality through tests, code review, observability, and simpler designs.
</li><li>Use data and production evidence to validate decisions.
</li>Take ownership of incidents and production issues when systems do not behave as expected. 
<li>
</li></ul> 
<h2 class="jobSectionHeader">What We Are Looking For
</h2><ul><li>Strong senior-level engineering judgment.
</li><li>Experience owning ambiguous technical work.
</li><li>Ability to solve problems across multiple layers of a system.
</li><li>Strong backend engineering experience with production services.
</li><li>Enough frontend experience to work on product-facing workflows when needed.
</li><li>Comfort with distributed systems, event-driven flows, caching, retries, rate limits, and failure modes.
</li><li>Strong production debugging skills.
</li><li>Ability to explain trade-offs clearly.
</li><li>Bias toward simple, reliable solutions.
</li>Good communication during incidents, reviews, and cross-team work. 
<li>
</li></ul> 
<h2 class="jobSectionHeader">Technical Experience
</h2><ul><li>5+ years of software engineering experience.
</li><li>Strong experience with Java, Scala, Kotlin, Go, or a similar backend language.
</li><li>Experience building APIs, services, and integrations.
</li><li>Experience with SQL and data-backed product behavior.
</li><li>Experience with GCP, AWS, or another cloud platform.
</li><li>Experience with Kafka, RabbitMQ, Pub/Sub, or similar event systems.
</li><li>Experience with logs, metrics, dashboards, alerts, and tracing.
</li>Experience writing automated tests and reviewing code. 
<li>
</li></ul> 
<h2 class="jobSectionHeader">Useful Experience
</h2><ul><li>React / TypeScript or similar frontend experience.
</li><li>Experience with merchant-facing or customer-facing product workflows.
</li><li>Experience with third-party integrations, account linking, OAuth, or external APIs.
</li><li>Experience with Redis, caching, rate limiting, queues, or high-volume event processing.
</li>Experience with analytics, reporting, attribution, or event data products. 
<li>
</li></ul> 
<h2 class="jobSectionHeader">Mindset
</h2><ul><li>Own the outcome, not only the ticket.
</li><li>Ask what problem we are solving before choosing the implementation.
</li><li>Prefer simple designs that other engineers can operate.
</li><li>Validate risky assumptions early.
</li><li>Use production data and customer impact to guide decisions.
</li><li>Escalate early when risk, ownership, or scope is unclear.
</li>Do not take shortcuts around process, security, or production safety. 
<li>
</li></ul> 
<h2 class="jobSectionHeader">What Good Looks Like
</h2>A strong candidate can describe systems they owned, incidents they handled, trade-offs they made, and mistakes they learned from.
They should be able to explain how they approach unclear problems, reduce risk before production, and make systems easier for the team to operate.
They should not need a tech lead to turn every ambiguous problem into a detailed task list.
<h1 class="jobSectionHeader">Inclusion and Belonging
</h1>At Commerce, we believe that celebrating the unique histories, perspectives and abilities of every employee makes a difference for our company, our customers and our community. We are an equal opportunity employer and the inclusive atmosphere we build together will make room for every person to contribute, grow and thrive.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the interview process, to perform essential job functions and to receive other benefits and privileges of employment. If you need an accommodation in order to interview at Commerce, please let us know during any of your interactions with our recruiting team.
Learn more about the Commerce team, culture and benefits at https://www.commerce.com/careers/
<h1 class="jobSectionHeader">Protect Yourself Against Hiring Scams: Our Corporate Disclaimer
</h1>Commerce, along with many other employers, has become the subject of fraudulent job offers to hopeful prospective job seekers.
 
 
Be advised:
 
Commerce does not offer jobs to individuals who do not go through our formal hiring process.
 
 
Commerce will never:
<ul><li>require payment of recruitment fees from candidates;
</li><li>request personally identifiable information through unsanctioned websites or applications;
</li><li>attempt to solicit money from you as part of the hiring process or as part of an employment offer;
</li><li>solicit money to complete visa requirements as part of a job offer. 
</li></ul> 
If you receive unsolicited offers of employment from Commerce, we urge you to be extremely cautious and avoid engaging or responding.</div>

Senior Software Engineer

Hiscox

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

Lead Data Scientist

<div>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.
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.
Responsibilities:<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>
Requirements:<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> 

Benefits 
<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

Quantspark

<div>Title: Engineering Manager 
Reporting to: Head of Engineering 
Office Environment: Hybrid, Central London Office 
Type: Full time, Permanent<h2 class="jobSectionHeader"> 
About QuantSpark</h2>
QuantSpark is an award-winning AI and data consultancy, but we don't just advise, we build. We help businesses in the UK and beyond, as well as governments, apply data, analytics and AI for measurable human and societal benefit, not just profit. This means tackling real-world challenges, innovating at scale, and forging solutions that deliver real impact to our clients.
Our culture is built on meritocracy of ideas, where the best thinking wins regardless of seniority, a place where intelligent failure is treated as something to learning form, and where we seriously invest in people with opportunities for career acceleration, ownership over projects, and a personalised &pound;6K per year L&amp;D budget. We&rsquo;ve recently been named as finalist in the Culture 100 Awards, shortlisted from more than 5,200 UK companies, with 93% of our team rating their experience here positively in May 2026.<h2 class="jobSectionHeader"> 
Our Client Portfolio</h2>
We work with prestigious, high-growth organisations and sector leaders, in the UK and internationally:<ul><li>Financial Services &amp; Private Equity: Delivering AI-powered analytics, risk, and operational tools.</li><li>Retail &amp; Consumer Brands: Optimising pricing, inventory, and engagement through actionable analytics.</li><li>Asset Management: Developing investment infrastructure and automated risk management systems.</li><li>Public Sector: Trusted by government departments for fraud analytics, predictive maintenance, and operations optimisation.</li><li>SaaS &amp; Manufacturing: Driving technological transformation and efficiency across verticals.</li></ul><h2 class="jobSectionHeader"> 
The Role</h2>
As Engineering Manager, you'll lead a team of 4 Data Engineers, 1 AI Engineer and 1 QA, and sit on the wider management team. A good portion of your week will be the coaching and line-managing of that team, growing people, unblocking them and holding the bar on quality. The rest will be spent delivering across a mix of client engagements and our own product development. This is a player-coach role, not pure people management, you'll stay hands-on enough to make architectural calls, review code and step in on the hard problems when needed.
Using AI well is core to the job, knowing where it genuinely adds value, where it doesn't, and how to embed it sensibly into how your team delivers and what you build for clients, without cutting corners on quality, security or judgement.<ul><li>Oversee and architect delivery of multiple software and data projects, ensuring scalability, security, and maintainability.</li><li>Guide and mentor engineers from junior to senior level, fostering technical growth and a high-performance culture.</li><li>Champion the practical, responsible adoption of AI across engineering workflows, tooling, and client solutions.</li><li>Partner with product managers and technical leads on deliverables, resourcing, and timelines.</li><li>Drive innovation in engineering processes, promoting best practices, DevOps, and technical standards.</li><li>Operate calmly between competing priorities, making clear trade-offs across delivery, people, and quality.</li><li>Engage with client stakeholders, managing partnerships and ensuring solutions are adopted.</li></ul> 
You Should Hit the Apply Button If
We're a lean consultancy scaling deliberately. A lot of what you'd take for granted at a larger firm is still yours to build such as engineering standards, delivery processes, tooling, the shape of the team itself. We move fast, we take on hard problems that often the bigger consultancies haven&rsquo;t been able to solve. You will have real autonomy and a genuine say in how engineering works at QuantSpark, but you'll also be building the road as you drive it. That calls for someone comfortable with ambiguity, willing to make the call on imperfect information, and is ready to get hands on, helping to build the organisation.<ul><li>You excel at managing teams, understand 'culture add' and how to inspire and coach a team to do their best work.</li><li>You bring hands-on experience across software and data &mdash; for example Python (Flask/Django), React.js, and analytics/data engineering (building pipelines, models, and data products).</li><li>You're fluent in software and data architecture, containerisation, and cloud platforms (AWS/Azure).</li><li>You understand the value of AI and know how to use it wisely, helping your team pick the right tools for the right problems.</li><li>You've managed cross-functional teams, mentored engineers, and championed technical and professional growth.</li><li>You can hold competing priorities at once and still keep a team focused, motivated, and performing.</li><li>You're passionate about DevOps and modern tooling, continuously pushing on process and code quality.</li></ul> 
I Want to Work for a Company That<ul><li>Balances visionary leadership with hands-on technical impact.</li><li>Prioritises impactful work and an innovative culture.</li><li>Treats AI as a tool to be used thoughtfully, not a box to be ticked.</li><li>Builds solutions that create lasting impact in both business and society.</li></ul> 
I'm Looking to Work With<ul><li>Smart, collaborative, cross-disciplinary teams solving complex business and technical problems.</li><li>Partners and clients who value AI and data-driven transformation.</li><li>Leadership that inspires, trusts, and invests in emerging talent.</li></ul> 
In 3&ndash;5 Years I Want to Be<ul><li>Recognised for delivering impactful work that matters to clients and the business.</li><li>A recognised mentor who's grown talented engineers and future leaders.</li><li>An influential leader connecting strategic decisions with the smart use of technology and AI.</li></ul><h2 class="jobSectionHeader"> 
Perks &amp; Benefits</h2><ul><li>&pound;6,000 annual training/conference allowance</li><li>Matched pension contributions up to 6%</li><li>Private Healthcare (Vitality)</li><li>EMI share options&mdash;own a part of QuantSpark&rsquo;s growth</li><li>Work abroad up to one month every year</li><li>25 days annual leave (+ bank holidays with the option to buy/sell up to 5 days)</li><li>Annual volunteering day</li><li>Cycle-to-work scheme</li><li>Central London office with socials &amp; events</li><li>Discounts with major retailers, tech, fitness, travel partners</li></ul><h2 class="jobSectionHeader"> 
Equal Opportunities</h2>
We are committed to building a diverse and inclusive team. Different perspectives, identities, and experiences make us stronger&mdash;both as people and as a business. All qualified applicants will be considered regardless of sex, sexual orientation, marital status, race, nationality, religion, disability, or age.</div>

Engineering Manager

<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 
As AI moves from experimentation to enterprise-wide adoption, doing it responsibly has become a commercial necessity, not just an ethical one. We are looking for a Responsible AI Specialist to ensure the solutions we design and the advice we give to clients are trustworthy, compliant, and fair by design. This is a role for someone who can translate principles (fairness, transparency, accountability) into practical frameworks that engineering teams and clients can actually apply.
You will be a connective figure across the practice: advising delivery teams on ethical and regulatory risk, contributing to client governance conversations, and helping shape the standards by which we build. You do not need to be a deep technical engineer, but you must understand how AI systems work, where they fail, and what good governance looks like in practice, particularly as regulation such as the EU AI Act reshapes expectations.
This is a growing area of strategic importance, offering significant scope to define our approach and to become a recognised voice in responsible AI.
Required skills &amp; experience:<ul><li>
Define and implement Responsible AI frameworks, policies, and practical guidelines across the practice.</li><li>
Advise project teams on ethical AI design, risk identification, and mitigation throughout the delivery lifecycle.</li><li>
Conduct AI risk and impact assessments, and embed fairness, transparency, and accountability into solutions.</li><li>
Contribute to client conversations on AI governance, risk, and regulatory readiness.</li><li>
Monitor evolving regulation (EU AI Act, ICO guidance, emerging standards) and translate it into actionable guidance.</li><li>
Support internal capability building, raising awareness and competence in responsible AI across teams.</li><li>
Partner with architects and data scientists to operationalise governance &mdash; model documentation, evaluation, and guardrails.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 3 years in AI ethics, governance, policy, risk, compliance, or a closely related regulatory field.</li><li>
Sound understanding of AI concepts, risks, and failure modes (deep technical implementation not required).</li><li>
Working knowledge of relevant regulation and standards, including the EU AI Act.</li><li>
Strong stakeholder communication skills, able to engage both technical teams and senior business audiences.</li><li>
Ability to turn principles into pragmatic, usable frameworks and processes.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Experience in consulting or advisory roles.</li><li>
Familiarity with assurance frameworks (ISO/IEC 42001, NIST AI RMF).</li><li>
Background in data protection, privacy, or model risk management.</li><li>
Exposure to fairness, bias, and explainability tooling.</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:
Responsible AI is central to how we earn client trust and differentiate our practice. You will have the rare chance to shape this capability from an influential position, combining ethics, regulation, and real delivery in work that genuinely matters. As adoption and scrutiny grow, so will your impact and your profile.</div>

Responsible AI Specialist (Governance, Ethics & Compliance)

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