data science team lead

Houseful

<div>Alto Software Group is a B2B SaaS company that powers more than half of all UK housing transactions each year. We create software solutions that connect businesses and consumers, delivering a one-stop shop for estate agents and home builders. Our goal is to drive efficiency, speed up transactions, reduce risk, and improve the end-customer experience. While we&rsquo;re not a start-up, we have a start-up mindset and want our people to operate with this mindset so that we can achieve our ambitions.
The Role
We are looking for a Data Science Lead to build and lead Alto&rsquo;s data science capability from the ground up. We have rich data flowing through our Mission Control platform and a clear commercial ambition to turn it into predictive insight &mdash; this hire gives us the leadership and technical depth to make that happen. You&rsquo;ll work at the intersection of data, product, and commercial strategy, with direct access to executive leadership and a platform that&rsquo;s ready to be exploited.
What You&rsquo;ll Do<ul><li>Define and own Alto&rsquo;s data science roadmap, prioritising use cases based on measurable ROI and commercial impact.</li><li>Build, deploy and maintain production-grade predictive models across churn, customer health, propensity and capacity forecasting.</li><li>Design and analyse experiments to test pricing, product and operational changes, raising the standard of statistical rigour across the business.</li><li>Partner with Platform and Data Engineering to productionise models on Mission Control, defining data quality and feature requirements for reliable modelling.</li><li>Develop segmentation and scoring frameworks that Customer Operations and Commercial teams can act on directly.</li><li>Work with the Head of AI Operations to identify automation opportunities grounded in data science outputs.</li><li>Surface insights through ThoughtSpot and AI-enabled reporting for senior stakeholders, up to executive level.</li><li>Mentor analysts and grow data science capability across the business, building a team rather than a one-person silo.</li></ul>
Who You Are<ul><li>A Builder: You don&rsquo;t just advise on data science &mdash; you write production code, ship models, and take personal accountability for outputs that are actually used.</li><li>Commercially Sharp: You understand SaaS metrics (MRR, churn, NRR, GRR) and have personally connected data science work to measurable business outcomes, not just model performance.</li><li>A Technical Authority: You bring expert-level Python and SQL, a solid grounding in statistics and causal inference, and a track record of models in production &mdash; not just notebooks.</li><li>Cross-Functionally Effective: You move comfortably between engineering, commercial, and operational stakeholders, translating between data science and business outcomes without losing either audience.</li><li>Outcome-Focused: You prioritise ruthlessly, track ROI on your work, and resist the pull of interesting-but-unactionable projects.</li><li>Comfortable in Ambiguity: You can define the problem as well as solve it &mdash; you don&rsquo;t need a fully formed brief to make progress, and you bring structure where there isn&rsquo;t any.</li></ul>
Our Technology Stack
Languages<ul><li>Python, SQL</li></ul>
BI &amp; Reporting<ul><li>ThoughtSpot</li></ul>
Platform<ul><li>Mission Control (Alto&rsquo;s internal data platform)</li></ul>
AI / ML<ul><li>Modern ML frameworks; experimentation and causal inference tooling; LLMs and practical AI applications</li></ul>
Why Join Alto?
This is a rare opportunity to build a data science function with a blank sheet, executive sponsorship, and a data platform already in production. You&rsquo;ll have the mandate and the access to make data science a structural part of how Alto operates &mdash; from retention and pricing to operational efficiency and intelligent automation. For a technically strong data scientist who wants to lead, not just contribute, this is that role. 
Benefits<ul><li> 
Hybrid &mdash; 2 days/week in London HQ</li><li>Everyday Flex &mdash; greater flexibility over where and when you work</li><li>25 days annual leave &mdash; plus extra days for years of service</li><li>Day off for volunteering &amp; Digital detox day</li><li>Festive Closure &mdash; business closed between Christmas and New Year</li><li>Cycle to work and electric car schemes</li><li>Free Calm App membership</li><li>Enhanced Parental leave</li><li>Fertility Treatment Financial Support</li><li>Group Income Protection &amp; private medical</li><li>Gym on-site in London</li><li>7.5% pension contribution by company</li><li>Discretionary annual bonus up to 10% &mdash; of base salary</li><li>Talent referral bonus up to &pound;5K</li></ul></div>

Data Science Lead

Penta

<div><h4 class="jobSectionHeader">What&rsquo;s in it for me?
</h4><ul><li>Competitive salary and compensation structure</li><li>
Generous paid time off and holiday schedule</li><li>
Frequent firm-wide social events and activities</li><li>
Excellent environment for learning and growth</li><li>
Further benefits, depending on location</li></ul><h4 class="jobSectionHeader"> 
About the Role</h4><div>
We are looking for a hands-on technical leader to lead Penta&rsquo;s Data Science team: someone who still designs, builds and reviews real solutions while owning execution, delivery and team development. You will be accountable for turning data science capability into shipped, dependable value for our clients and advisory teams, in alignment with our product roadmap. 
 
Penta&rsquo;s technology makes client outcomes sharper, faster, more differentiated and harder to replace. The Data Science team&rsquo;s success is measured by how much it improves live client work, not by technical elegance in isolation. 
 
Our core data science focus is natural language understanding at scale, processing millions of articles daily across stakeholder sentiment, topic identification over time, competitive peer-set selection, summarisation, contextualisation and other processing of unstructured content. Most use cases are creative chains of multiple steps drawn from data processing, exploratory analysis, fundamental ML, NLP, SQL, LLMs and integration into our live systems.</div> 

What you&rsquo;ll do 
 
Lead the team<ul><li>
Manage, coach and develop Penta&rsquo;s Data Science team, setting priorities, planning capacity and creating a high-trust, high-output delivery culture.</li><li>
Translate the product roadmap and advisory needs into a focused data science plan, partnering with Product, Advisory, Database, Development and DevOps teams to keep delivery aligned with client outcomes.</li><li>
Raise the delivery bar for execution, quality, pace, maintainability and cost discipline.</li></ul>
Ship production data science and AI systems<ul><li>
Design, build and review data science solutions across NLP, LLM workflows, machine learning, SQL and large-scale content processing.</li><li>
Own technical design and architecture for data-science-enabled applications, ensuring solutions are maintainable, supportable, observable and easy to operate.</li><li>
Productionise delivery with DevOps and MLOps, automating deployment in AWS and puttinge evaluation, monitoring and provider-routing controls in place so AI outputs remain reliable and cost-effective.</li></ul>
Scale practical AI adoption<ul><li>
Design and implement AI workflows as skills, models and MCP tools in OpenWebUI, with cost control, provider routing and observability built in.</li><li>
Partner with other departments to turn AI capabilities into everyday workflows, reusable tools and knowledge layers that improve internal productivity and client delivery.</li><li>
Evaluate emerging AI tools, models and agentic patterns, bringing the useful ones into production quickly and responsibly.</li></ul><div>
Success in this role 
 
Means the Data Science team is shipping reliable, maintainable AI and analytics capabilities into live client and advisory workflows; team members are growing; delivery is predictable; and Penta&rsquo;s applied AI capability is visibly improving across products and engagements. 
 
The Team 
 
Our Technology team supports Penta&rsquo;s ambitious delivery plans, using technology to automate solutions, optimise outcomes and support continuous integration and deployment. The six-person Data Science team sits alongside Development, Engineering / DevOps &amp; Platform Security, IT and the PMO, and works hand in hand with the Product team. 
 
The environment is collaborative, pragmatic and delivery-focused. We move quickly, share ideas openly, and use regular hackathons and experiments to generate practical business value. 
 
This is the hands-on leadership role for that team. Reporting to the CTO, You will lead a team working at the frontier of applied AI and data science, combining production LLM workflows, advanced prompting, agentic tooling, NLP, ML and large-scale content processing. You will set its direction, raise its delivery bar, grow its people through hands-on coaching, and lead from the front by actively shaping and delivering the work yourself. 
 
Our approach to AI is practical 
 
We are forward-thinking and ambitious in practically applying AI across client-facing work, corporate teams, technology and data science. We do not train our own foundation models; we apply, orchestrate and evaluate the best available models from major providers, engineering them into robust workflows that solve real business problems. 
 
We validate and document our methodologies through white papers and technical explainers, setting out the academic and analytical foundations behind our products, and the evidence that supports their use. This helps build trust in our tools, why they work and shows how they can be applied. 
 
We build on open-source AI software, including LiteLLM and OpenWebUI, to maximise the internal value of AI and build durable institutional capability. Reliability, cost control, observability, instruction-following, usability and adoption matter most. 
 
The team designs reusable workflows, skills, models and MCP tools that support Penta&rsquo;s move towards an AI-native advisory operating system. Keeping Penta at the forefront of practical AI in PR, communications and strategic consultancy is part of the role.</div><h4 class="jobSectionHeader">
About You</h4>
Tech skills required: applied AI, LLMs and data science 
<ul><li>
Advanced Python coding for data science</li><li>
Power-user fluency with frontier AI tools, especially Claude: expert-level prompting, context engineering, agentic workflows, model selection, evaluation, and practical use of the latest AI- native data science techniques</li><li>
Practical experience engineering production LLM workflows, including prompt / skill design, evaluation, cost control, provider routing, agentic / human-in-the-loop orchestration, embeddings, vector search and RAG</li><li>
Implementation of foundational ML algorithms, classic NLP techniques and LLMs</li><li>
Strong SQL for analytical and production use, ideally PostgreSQL, including complex joins, CTEs and aggregation</li><li>
AWS: EC2, ECS, S3; DevOps and automated deployment</li><li>
Git version control</li><li>
Ideally experience with OpenWebUI, LiteLLM, MCP tools and/or Claude Code</li></ul>
Key competencies &amp; experience<ul><li>
Significant hands-on experience as an Applied AI / Data Science technical leader, with recent, practical experience using frontier LLMs, prompting and agentic workflows to ship production systems. Typically this will mean around 10+ years&rsquo; hands-on experience, with technical-leadership exposure.</li><li>
A suitable degree, ideally in Software Engineering or a related technical field, and the technical grounding set out above will round out the profile.</li></ul>
The successful candidate will also have:<ul><li>
an analytical and logical mind, dynamic, positive and ready to make a difference;</li><li>
the ability to communicate complex technical topics clearly to senior, non-technical and technical audiences;</li><li>
a passionate drive for code quality, results and getting work shipped, with sound judgement on build-vs-buy, prioritisation and balancing speed against maintainability, cost and risk.</li></ul>
We strongly believe in developing talent and are willing to invest time to develop the people who join our team.<h4 class="jobSectionHeader">
About us</h4>
Penta Group is a global company providing data-driven solutions to help clients achieve their objectives in an increasingly complex stakeholder environment. We provide cutting-edge intelligence products to help clients understand what their stakeholders think, see, and hear, and then leverage that intelligence to develop and execute effective, measurable strategies. 
 
Our global team brings decades of experience in business, government, communications, research, data science, and media. Our clients include companies across a variety of industries, including technology, financial services, energy, healthcare, and more. Penta has offices in New York, London, Washington, DC, San Francisco, Dublin, London, Brussels, Singapore, and Hong Kong.</div>

VP, Head of Data Science

Wayflyer

<div>
 
 About Wayflyer
 
 
 
 Today's small businesses need a capital provider that keeps pace with their growth ambitions. Traditional financing options are slow, cumbersome and often out of reach. That's why we built Wayflyer.
 
 
 Our technology allows us to assess businesses in minutes, generate financing offers that reflect their growth potential and send funds in as little as 24 hours. To date, we've deployed over $6bn to thousands of businesses worldwide, backed by Tier 1 banks like J.P. Morgan.
 
 
 You'll be collaborating with ambitious colleagues from around the world. We have offices in Dublin, London, New York, Charlotte, Berlin and Sydney.
 
 
 
 The challenge
 
 
 
 Data Science at Wayflyer isn't a research function sitting outside the business - it's embedded in the decisions that determine who we fund, how we price, and how fast we grow. We have a team of talented Data Scientists and ML Engineers doing serious work. Now we need someone who can lead them, raise the bar, and make sure what they build actually ships and sticks.
 
 
 
 What You'll Actually Do
 
 
 
 We treat Machine Learning as a branch of software engineering, so you'll be a hands-on technical leader, not someone who manages from a distance. You'll write code, review PRs, and take responsibility for the production-grade ML models that power Wayflyer's go-to-market and funding processes.
 
 
 <ul>
 <li>
 Manage, mentor and scale a team of 4+ DS/ML engineers, holding the bar on technical excellence and code quality
 </li>
 <li>
 Own the ML lifecycle end to end, from dataset annotation and model training through to deployment, monitoring and infrastructure
 </li>
 <li>
 Partner with Product and Engineering leads to shape a data science roadmap that actually moves the business
 </li>
 <li>
 Put engineering discipline behind the work: reproducible pipelines, automated testing, documentation that holds up
 </li>
 <li>
 Translate complex technical work into something VPs and the C-suite can act on
 </li>
 <li>
 Push your team to use AI and LLMs to get to better outputs faster, not as a substitute for thinking
 
 
 </li>
 </ul>
 
 Who Thrives Here
 
 
 
 You started as an individual contributor and you haven't forgotten what it feels like to be in the weeds of a model that won't behave. You lead from the front, your team knows you can do the work, which is why they trust your direction on it. You can hold a technically rigorous standard and a commercially pragmatic one at the same time, and you know when to push back on a roadmap request and when to find a way to say yes. The people you've managed would say you made them better.
 
 
 <ul>
 <li>
 Advanced Python and SQL, the kind you'd expect from a strong Software Engineer
 </li>
 <li>
 Real experience getting models deployed, monitored and running reliably in production (Airflow, Dagster or similar)
 </li>
 <li>
 A proven track record of building and maintaining production ML systems yourself.
 </li>
 <li>
 Ability to translate business challenges (specifically in risk or growth) into technical data solutions.
 
 
 </li>
 </ul>
 
 How You&rsquo;ll Stand Out
 
 
 
 <ul>
 <li>
 Stack: Python, SQL, Modern Data Stack, Orchestration tools.
 </li>
 <li>
 Bonus: Experience in FinTech or Credit Risk.
 </li>
 <li>
 Bonus: Experience with NLP (Text classification, NER).
 
 
 </li>
 </ul>
 
 What This Role Could Turn Into
 
 
 
 This is a role with a direct line to how Wayflyer scales. As the business grows, so does the scope: more products, more markets, more decisions that need Data Science at their core. The person who lands this role won't just be running a team, they'll be shaping how data science is practiced across the organisation. That might mean:
 
 
 <ul>
 <li>
 Expanding into adjacent domains like growth or platform
 </li>
 <li>
 Taking ownership of cross-functional initiatives
 </li>
 <li>
 Setting the standards other teams build to
 
 
 </li>
 </ul>
 
 We hire for range
 
 
 
 We're less interested in years served than in the arc that got you here. You've probably gone from building models yourself to building the team that builds them, and you're still just as comfortable doing both. You've led a data science or ML team before, and you still write code, and you've got the judgment to know what great looks like at every stage of the ML lifecycle.
 
 
 
 Location and working policy
 
 
 
 
 📍
 
 Dublin or London, Hybrid.
 
 
 
 The good stuff
 
 
 
 25 days off, plus public holidays. Private healthcare, life insurance, and a pension. Equity - because you should own a piece of what you're building. Generous parental leave for primary and secondary caregivers. 60 days a year to work abroad from wherever you want.
 
 
 
 By submitting your application, you acknowledge that Wayflyer Limited will process your personal data for the purpose of evaluating your suitability for the role. Such processing is based on the need to take steps prior to entering into a potential employment agreement. To learn more about how we handle your personal data, you can contact our privacy team at
 
 
 privacy@wayflyer.com
 
 
 or review our privacy notice at
 
 
 https://wayflyer.com/privacy-notice
 
 
 .
 
</div>

Data Science

<div><div><h4 class="jobSectionHeader">Who We Are</h4>

WPP Enterprise Solutions designs, builds, and operates the growth systems that competitive businesses rely on. In a world where Al is reshaping how companies drive growth, we lead clients in business transformation and marketing modernization, connecting strategy directly to execution. Our 12,000 experts in engineering and platforms, commerce, consulting, content transformation, CRM, and CX work within a unified global operating unit across 40+ markets. WPP Enterprise Solutions works alongside best-in-class partners including Adobe, AWS, Braze, Google, Microsoft, Salesforce, and Shopify, as well as innovators in AI, to deliver growth solutions tailored to the needs of our clients' businesses.</div>
We're looking for a Lead Data Scientist and manager of the practice to lead this next chapter. You'll own the data science practice end-to-end; building and managing the team, advising clients on what's possible, and delivering work that raises the bar for what data can do within marketing ecosystems.

Client demand is growing. And you'll have real autonomy to shape what this practice becomes: the product offering, the ways of working, and how data science becomes an accelerator that elevates the work of activation, engineering, and insights teams around you.
<h2 class="jobSectionHeader">
What will your day look like?</h2>
<ul><li>Lead &amp; Grow the Team: Manage a team of data scientists end-to-end; hiring, onboarding, personal development, performance conversations, and day-to-day support. Coach team members technically and professionally. 
Identify skill gaps, plan for future needs, and scale the team as the practice grows. Foster a culture of knowledge sharing, curiosity, and quality.</li>
</ul><ul><li>Build, Not Just Oversee: Personally contribute to high-complexity initiatives; designing and shipping ML models, training and inference pipelines, and experimentation frameworks. Bring deep, hands-on expertise in marketing-relevant techniques: uplift modelling, propensity scoring, attribution, next best action, segmentation, causal inference, and recommender systems. Set the technical bar through code and craft, not just review.</li>
</ul><ul><li>Advise Clients Strategically: Partner with account and strategy teams on scoping, proposals, and commercial conversations: you're a credible voice in the room when clients are deciding where to invest. 
Act as a trusted data advisor. Proactively identify gaps and untapped opportunities in clients' data and marketing ecosystems. Translate complex findings into business recommendations. 
Anticipate business needs and challenges; build lasting client relationships as the go-to person for data science matters.</li>
</ul><ul><li>Deliver End-to-End with Quality: Lead complex data science initiatives from hypothesis and experimentation through model development, validation, and activation. Collaborate closely with Data Engineers and Architects so solutions are grounded in solid infrastructure. Own quality across all team deliverables, with discipline in statistical methods, reproducibility, and insight generation.</li>
</ul><ul><li>Lead the team into Agentic AI: Champion agentic AI as both a way of working and a delivery capability. Coach data scientists to adopt AI-native engineering practices (agentic coding, AI-assisted development, prompt and context engineering) and lead the design of agentic solutions for clients: from internal accelerators to production-grade agents embedded in marketing workflows. We expect you have shipped or prototyped agentic solutions and have a clear point of view on where they create real value.</li>
</ul><ul><li>Apply CRM &amp; Marketing Domain Expertise: Contextualize data science within clients' CRM, campaign, and personalization strategies. Leverage hands-on experience with platforms like Adobe AEP, Salesforce Data Cloud, or Braze to extend marketing measurement and influence communications from a data perspective.</li>
</ul><ul><li>Shape the Practice: Establish guidelines, ways of working, and reusable accelerators. Maintain a backlog of data science use cases. Contribute to roadmapping, maturity frameworks, and the data science product catalogue alongside the Global Data Practice Lead.</li>
</ul><h2 class="jobSectionHeader">Who are you going to work with?</h2>

You will lead a small, technically capable team of data scientists who need a manager with both technical credibility and genuine investment in their growth. Beyond your team: Data Engineers, Architects, Strategy Consultants, Account teams, and clients directly.
<h2 class="jobSectionHeader">
What do you bring to the table?</h2>

Data Science &amp; Technical
<ul>
<li>5&ndash;8 years of hands-on data science experience combining technical depth with client advisory.</li>
</ul><ul><li>Strong expertise in statistical analysis, experimentation, ML techniques (regression, classification, clustering, hypothesis testing, next best action modelling).</li>
</ul><ul><li>Proficiency in Python and advanced SQL.</li>
</ul><ul><li>Solid grasp of adjacent domains: data modelling, ETL/ELT strategy, no-SQL databases, pipeline design&mdash;enough to collaborate credibly with engineers and architects.</li>
</ul><ul><li>Domain knowledge in CRM and marketing technology: campaign metrics, measurement frameworks, and experience with platforms such as Adobe, Salesforce, or Braze.</li>
</ul><ul><li>Cloud platform experience (GCP, AWS, or Azure).</li>
</ul>
Advisory &amp; Business
<ul>
<li>Consulting craft: Run client conversations end-to-end &mdash; scoping problems, shaping proposals, writing SOWs, contributing to RFPs, and defending recommendations under challenge. Comfortable moving between boardroom narrative and technical detail in the same meeting. Prior consulting or agency experience expected.</li>
</ul><ul><li>Commercial &amp; advisory instinct: Track record of identifying data-driven opportunities, building maturity roadmaps, and translating data science into business outcomes. Sound judgement on effort, ROI, and prioritisation by impact.</li>
</ul>
People Management
<ul>
<li>Demonstrated experience managing a team: mentoring, performance reviews, hiring, and day-to-day support. Formal management experience is essential.</li>
</ul><ul><li>Coaching-oriented leadership style. You grow people through trust, feedback, and investment&mdash;not top-down direction.</li>
</ul><ul><li>Comfort scaling a team that's still taking shape: anticipating needs, defining roles, onboarding effectively.</li>
</ul><ul><li>Emotional intelligence, empathy, and conflict resolution skills.</li>
</ul>
Excellent communication skills in English.

Nice to Have
<ul>
<li>Agency or consultancy experience in fast-paced, multi-client environments.</li>
</ul><ul><li>CRM certifications (e.g., Adobe CJA, RTCDP).</li>
</ul><ul><li>Familiarity with data governance and privacy (GDPR, CCPA).</li>
</ul><ul><li>Experience with out-of-the-box vendor intelligent services.</li>
</ul><ul><li>Exposure to agentic AI or AI-driven automation use cases.</li>
</ul><ul><li>Management or leadership certifications.</li>
</ul><h2 class="jobSectionHeader">A leader in personalized customer experiences</h2>

VML MAP is a world-leading Centre of Excellence that helps businesses humanize the relationship between the brand and the customer through hyper personalization at scale, marketing automation and CRM. With the brain of a consultancy, the heart of an agency and the power of technology and data, we work with some of the world's most admired brands to help them on their transformation journey to becoming truly customer-centric. Together, we are 1000 + technology specialists, data scientists, strategic thinkers, consultants, operations experts, and creative minds from 55+ nationalities.
<h2 class="jobSectionHeader">
A global network</h2>

We are part of the global VML network that encompasses more than 30,000 employees across 150+ offices in 60+ markets, each contributing to a culture that values connection, belonging, and the power of differences.

#LI-EMEA<div>
About WPP

WPP is the trusted growth partner for the world's leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company &ndash; powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. For more information, visit WPP.com.

WPP (MAP/VML) is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

When you click &quot;Apply now&quot; below, your information is sent to MAP/VML. To learn more about how we process your personal data during when you apply for a role with us, on how you can update your information or have the information removed please read our Privacy policy. California residents should read our California Recruitment Privacy Notice.</div></div>

Senior Manager - Data Science (Martech/CRM)

Brainlabs

<div><div>Brainlabs is the media agency built to answer one question: what's actually driving profit? Founded in 2012 by Daniel Gilbert, we were built by engineers before we were a media agency. Today, 1,000+ Brainlabbers across five continents use our proprietary agents, built on 32 media tools and over 2,500 logged experiments, to help brands connect every channel they plan and buy to one thing: the bottom line.</div>
As the Director, Data Science, you will lead Brainlabs' Marketing Mix Modelling capability, overseeing the deployment of Google Meridian and other advanced modelling projects for our clients. You are accountable for the technical rigour of our data science output and for translating complex statistical findings into clear, commercially actionable insight that clients can use to make better decisions with their media budgets. Working at the intersection of advanced analytics and senior client engagement, you will build our data science practice and establish Brainlabs as the agency partner that makes MMM work in practice, not just in theory.
<h3 class="jobSectionHeader">
What you do</h3>
<ul><li>Lead MMM Deployments: You own the end-to-end delivery of Google Meridian and other MMM projects for clients, from initial scoping and data preparation through to model calibration, scenario planning, and insight presentation.</li>
<li>Develop and Deliver Modelling Projects: You scope and lead a broader range of data science engagements beyond MMM, identifying where advanced modelling can solve real client problems and designing solutions that are technically sound and commercially relevant.</li>
<li>Translate Complexity Into Action: You distil the outputs of complex statistical models into narratives that senior client stakeholders can understand and act on, connecting model findings directly to media budget decisions and business strategy.</li>
<li>Drive AI Adoption Across the Team: You lead the integration of AI tools, including Claude, into the data science team's ways of working &mdash; from accelerating code development and model documentation to improving how technical outputs are packaged and communicated to clients.</li>
<li>Own Senior Client Relationships: You are Brainlabs' senior data science point of contact for key clients, presenting findings and recommendations at CMO and VP level and building confidence in our analytical approach.</li>
<li>Build and Lead the Data Science Team: You manage and develop a team of data scientists, setting technical standards, running structured development conversations, and ensuring the team's output meets the quality bar the practice needs.</li>
<li>Grow the Practice: You drive the development of Brainlabs' data science proposition, contributing to new business pitches, publishing thought leadership, and building the processes that allow the practice to scale.</li>
</ul><h3 class="jobSectionHeader">Who you are</h3>
<ul><li>An MMM Expert: You have extensive, hands-on experience with Marketing Mix Modelling, including working knowledge of Meridian, Robyn, and/or PyMC, and a track record of delivering MMM projects that have driven real client decisions.</li>
<li>Technically Proficient: You are fluent in Python and experienced with GCP, with a strong grounding in Bayesian statistics and the principles underpinning modern media attribution.</li>
<li>AI-Forward: You actively explore how AI tools can augment data science practice, from speeding up code development and model documentation to helping non-technical stakeholders engage more confidently with complex outputs.</li>
<li>A Skilled Communicator of Complexity: You can take the output of a sophisticated model and tell a story with it that a CMO finds compelling and a media team can act on, without sacrificing the integrity of the underlying analysis.</li>
<li>An Experienced Team Leader: You have led teams of data scientists, with a genuine commitment to their development and a clear view of what good technical mentorship looks like.</li>
<li>Commercially Astute: You understand how data science creates commercial value for clients and for Brainlabs, and connect technical decisions to business outcomes in conversations with senior stakeholders.</li>
<li>A Practitioner-Leader: You remain close to the technical work, not just the management of it, and hold yourself to the same standard of rigour you expect from your team.</li>
</ul><h3 class="jobSectionHeader">How you succeed</h3>
<ul><li>Client Outcomes: Clients can point to specific budget decisions informed by your modelling work, and you can evidence the incremental value delivered through the projects you lead.</li>
<li>Model Quality: Every MMM deployment you oversee meets a documented quality standard, with calibration, validation, and scenario outputs that you and your team can defend under scrutiny.</li>
<li>Clear Communication: Your data science outputs land with senior client stakeholders, evidenced by positive feedback and by clients returning to Brainlabs for further analytical work.</li>
<li>AI Adoption: You achieve documented AI adoption across the data science team's workflows, with clear evidence of time saved or quality improved as a result.</li>
<li>Team Development: The data scientists in your team are growing in capability, and you can point to specific examples of how your leadership has raised their technical standards or broadened their skills.</li>
<li>Practice Growth: You contribute to at least one new business pitch per quarter and publish thought leadership that builds Brainlabs' data science credentials in the market.</li>
<li>Commercial Impact: The data science practice grows its revenue and client base under your leadership, and you can evidence progress against agreed commercial targets over time.</li>
</ul><div>
What happens next?

We know searching for a job is tough and that you want to find the best career and employer for you. We also want to ensure that this position is the best fit for both you and us. Therefore, you will participate in a comprehensive interview process that includes skills interviews with our team. The goal of this process is to allow you to get to know us as we learn more about you.

Brainlabs actively seeks and encourages applications from candidates with diverse backgrounds and identities. We are proud to be an equal opportunity workplace: we are committed to equal opportunity for all applicants and employees regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion, or belief, and marriage and civil partnerships. If you have a disability or special need that requires accommodation during the application process, please let us know!

Please note that we will never ask you to transfer cash or make any other payment to us in order to apply for a role or to work for Brainlabs. Any such asks are fraudulent and should be reported to the appropriate authorities in your area.</div></div>

Director, Data Science

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

JPMorganChase

<div>JOB DESCRIPTION 
 
 
As a Lead Software Engineer for AI &ndash; Vice President at JPMorgan Chase in Risk Technology, you will lead a specialized technical area, driving impact across teams, technologies, and projects. You will leverage your expertise in software engineering, multi-agent system design, data science, and NLQ to deliver complex, high-impact initiatives. You will mentor and guide a team of engineers, foster best practices in AI engineering, and partner with data science, product, and business teams to deliver end-to-end solutions that drive value for the Risk business. 
 
Job Responsibilities
<ul><li>Lead the deployment and scaling of advanced generative AI and agentic AI solutions for the Risk business, with a focus on natural language querying of structured and unstructured data sources.</li>
<li>Design and execute enterprise-wide, reusable AI frameworks and core infrastructure to accelerate AI solution development, including NLQ capabilities for diverse data types.</li>
<li>Develop multi-agent systems for orchestration, agent-to-agent communication, memory, telemetry, guardrails, and NLQ-driven data retrieval and processing.</li>
<li>Guide research on context and prompt engineering techniques to improve prompt-based model performance and NLQ accuracy, utilizing libraries such as LangGraph.</li>
<li>Develop and maintain tools and frameworks for prompt-based agent evaluation, monitoring, and optimization at enterprise scale, with emphasis on NLQ workflows and orchestration.</li>
<li>Build and maintain data pipelines and processing workflows for scalable, efficient consumption and querying of structured and unstructured data via natural language interfaces.</li>
<li>Write secure, high-quality production code and conduct code reviews.</li>
<li>Partner with Data Science, Product, and Business teams to identify requirements and develop NLQ-enabled solutions.</li>
<li>Communicate technical concepts and results to both technical and non-technical stakeholders, including senior leadership.</li>
<li>Provide technical leadership, mentorship, and guidance to junior engineers, promoting a culture of excellence and continuous learning.</li>
</ul>Required Qualifications, Capabilities, And Skills
<ul><li>Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.</li>
<li>Experience in data science and natural language querying, including experience deploying end-to-end pipelines on AWS.</li>
<li>Strong proficiency in Python.</li>
<li>Hands-on experience in system design, application development, testing, and operational stability.</li>
<li>Experience using LangGraph for multi-agent orchestration and NLQ integration.</li>
<li>Experience with AWS and infrastructure-as-code tools such as Terraform.</li>
</ul>Preferred Qualifications, Capabilities, And Skills
<ul><li>Strategic thinker with the ability to drive technical vision for business impact.</li>
<li>Experience with agentic telemetry, evaluation services, and orchestration of NLQ workflows.</li>
<li>Demonstrated leadership working with engineers, data scientists, and AI practitioners.</li>
<li>Familiarity with MLOps practices and AI pipelines.</li>
<li>Hands-on experience building and maintaining user interfaces for NLQ and data exploration.</li>
</ul>ABOUT US
 
 
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. 
<div><div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. 
</div></div> 
 
ABOUT THE TEAM
 
 
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.</div>

Lead Software Engineer - AI for Risk Technology

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