data engineer

data scientist

senior data scientist

senior data engineer

analytics engineer

data science director

Brainlabs

<div><div><p>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.</p></div><p>
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.</p>
<h3 class="jobSectionHeader"><b>
What you do</b></h3>
<ul><li><b>Lead MMM Deployments: </b>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><b>Develop and Deliver Modelling Projects: </b>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><b>Translate Complexity Into Action: </b>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><b>Drive AI Adoption Across the Team: </b>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><b>Own Senior Client Relationships: </b>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><b>Build and Lead the Data Science Team: </b>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><b>Grow the Practice: </b>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"><b>Who you are</b></h3>
<ul><li><b>An MMM Expert: </b>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><b>Technically Proficient: </b>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><b>AI-Forward: </b>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><b>A Skilled Communicator of Complexity: </b>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><b>An Experienced Team Leader: </b>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><b>Commercially Astute: </b>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><b>A Practitioner-Leader: </b>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"><b>How you succeed</b></h3>
<ul><li><b>Client Outcomes: </b>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><b>Model Quality: </b>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><b>Clear Communication: </b>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><b>AI Adoption: </b>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><b>Team Development: </b>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><b>Practice Growth: </b>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><b>Commercial Impact: </b>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><p><b>
What happens next?</b></p>
<p>
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.</p>
<p></p>
<p><i>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!</i></p>
<p><i>
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.</i></p></div></div>

Director, Data Science

Dentsu

<div>The purpose of this role is to facilitate delivery of best in class analytic and data assessments and roadmaps per established processes and templates in concert with other business disciplines, to manage and develop the team and serve as a point of escalation as needed.<p></p><p><b>
Job Description:</b></p><div><div><p><b>
Role Overview</b></p></div><div><p>
Analytics is a core strategic capability within dentsu, enabling smarter decisions and sustainable growth for our clients. As a Global Analytics Director, you will have two focus areas:</p></div><div><p><br>
Client Impact: Deliver advanced analytics solutions that drive measurable business outcomes for global clients</p></div><div><p><br>
Solutions &amp; Innovation: Develop scalable analytics, AI and data science solutions that can be reused, productised and embedded across the dentsu network</p></div><p></p><div><p><br>
This is a hands-on leadership role combining technical expertise, product thinking and client engagement. You will translate complex data, modelling and AI capabilities into actionable insights, solutions and products that drive growth. You will work closely with the Global Analytics leads and cross-functional teams to evolve dentsu&rsquo;s analytics proposition, moving from bespoke delivery to scalable, AI-enabled solutions and products.</p></div><p></p><div><p><br>
Role &amp; Responsibilities</p></div><div><p>
1. Client Delivery &amp; Impact</p></div><div><ul><li><p>
Manage and execute analytics and data science solutions for global clients</p></li></ul></div><div><ul><li><p>
Develop and implement measurement frameworks, MMM, experimentation and optimisation approaches</p></li></ul></div><div><ul><li><p>
Translate complex analytical outputs into clear insights, recommendations and business actions</p></li></ul></div><div><ul><li><p>
Work with client teams to embed analytics into decision-making, planning and investment strategies</p></li></ul></div><p></p><div><p><br>
2. Product &amp; Solution Innovation</p></div><div><ul><li><p>
Design and develop reusable analytics products and solutions (e.g. growth models, planning tools, experimentation engines)</p></li></ul></div><div><ul><li><p>
Contribute to the development of dentsu&rsquo;s AI-enabled analytics suite (e.g. prediction engines, decisioning systems, agentic workflows)</p></li></ul></div><div><ul><li><p>
Translate repeatable client use cases into scalable modules, frameworks and toolkits</p></li></ul></div><div><ul><li><p>
Partner with data, technology and engineering teams to industrialise solutions, from prototype to production.</p></li></ul></div><div><ul><li><p>
Identify opportunities to embed automation, GenAI and agentic solutions into analytics workflows</p></li></ul></div></div><p></p><div><div><p><br>
3. Collaboration &amp; Integration</p></div><div><ul><li><p>
Work cross-functionally to support the integration of analytics into dentsu&rsquo;s growth products and planning solutions</p></li></ul></div><div><ul><li><p>
Collaborate with global and market teams to ensure solutions are adoptable, scalable and aligned to client needs</p></li></ul></div><div><ul><li><p>
Support new business pitches with analytics input.</p></li></ul></div><p></p><div><p><br>
4. Capability Building &amp; Thought Leadership</p></div><div><ul><li><p>
Contribute to the evolution of dentsu&rsquo;s analytics, AI and data science capability</p></li></ul></div><div><ul><li><p>
Develop and codify best practices, frameworks and playbooks</p></li></ul></div><div><ul><li><p>
Provide thought leadership on AI, modelling and measurement innovation internally and externally</p></li></ul></div><p></p><div><p><br>
Skills &amp; Experience</p></div><div><ul><li><p>
Previous experience in analytics, data, or research, ideally within a media or marketing environment.</p></li></ul></div><div><ul><li><p>
Experience applying AI and advanced analytics (predictive modelling, ML, and emerging GenAI approaches) to drive decision-making and automation</p></li></ul></div><div><ul><li><p>
Hands-on proficiency in data science tools and languages (eg.Python, SQL)</p></li></ul></div><div><ul><li><p>
Ability to translate analytical work into clear insights, recommendations and actions for non-technical stakeholders</p></li></ul></div><div><ul><li><p>
Strong commercial mindset, focused on impact, adoption and business outcomes, not just analysis</p></li></ul></div></div><p></p><p><b>
What we offer</b></p><ul><li><p>
This is a permanent role.</p></li><li><p>
This is a hybrid working role with the expectation that you will be in our London office 3 times a week.</p></li><li><p>
As well as a competitive salary, you&rsquo;ll enjoy a benefits package that you can tailor to your needs.</p></li></ul><p><b><br>
Inclusion and Diversity</b><br>
At Dentsu, we embrace diversity and inclusion, valuing the unique perspectives and contributions of every individual. We believe that diversity fuels creativity and innovation, benefiting our employees, partners, and communities.<br>
<br>
We welcome applications from all individuals, regardless of race, ethnicity, nationality, religion, gender, gender identity, sexual orientation, age, disability, marital status, or any other protected characteristic. Beyond recruitment, we strive to create an environment where everyone feels respected, supported, and empowered to bring their authentic selves to work.<br>
<br>
We recognize the importance of work-life balance and are open to discussing flexible working arrangements for all roles. If you need reasonable adjustments due to a disability or medical condition during our recruitment process, please contact us at accommodations@dentsu.com, quoting the reference number of the role that you are applying for. Your needs will be handled with respect and confidentiality to ensure an inclusive and accessible experience.<br>
<br>
<b>About Dentsu</b><br>
Taking a people-centered approach to business transformation, we use insights to connect brand, content, commerce and experience, underpinned by modern creativity. As part of Dentsu Group Inc. we are headquartered in Tokyo, Japan and our 65,000 employee-base of dedicated professionals work across four regions (Japan, Americas, EMEA and APAC). Dentsu combines Japanese innovation with a diverse, global perspective to drive client growth and to shape society.<br>
<br>
Diversity, equity, and inclusion sits at the heart of our Social Impact strategy &ndash; our fully integrated sustainability strategy which includes our ambition to build a fair and more equal society, where everyone is equipped to thrive.</p><p></p><p>
#LI-Hybrid</p><p></p><p><b>
Location:</b></p>
London<p></p><p><b>
Brand:</b></p>
Global Media<p></p><p><b>
Time Type:</b></p>
Full time<p></p><p><b>
Contract Type:</b></p>
Permanent</div>

Global Analytics Director

Novartis

<div><div><h3 class="jobSectionHeader"><b>Summary
</b></h3><div>Independently lead agentic AI initiatives within the SPPO Data Science and AI Strategy in Global Drug Development, directly contributing to faster delivery of transformative medicines to patients.<br>
<br>
Role model a culture of AI-augmented, data-driven decision-making across GDD functions &mdash; spanning clinical development, translational research, and regulatory.<br>
<br>
Deep technical expert with accountability for agentic AI systems that reduce time to insight and time to patient across global development programs.<br>
<br>
Shape the agentic AI direction for your organizational domain, grounded in the broader GDD strategy set by leadership.<br>
<br>
Where managing a team: empower, guide, and coach data scientists and AI engineers to deliver at the frontier of applied AI in drug development.</div>
</div><div><h3 class="jobSectionHeader"><b>About the Role
</b></h3><div><p><b>Internal job title:</b> Director</p><p><b>
Position Location</b>: Hybrid working arrangement, London <b>#LI-Hybrid</b></p><p></p><p>
This is a senior AI leader role within Novartis Global Drug Development (GDD), responsible for leading the design, build, and productionization of agentic AI systems &mdash; think multi-agent architectures, tool-using LLMs, and autonomous workflow orchestration &mdash; to accelerate drug development timelines and time-to-patient. The role sits at the intersection of deep technical expertise (agentic frameworks, RAG, governance, data foundations) and strategic influence, shaping the agentic AI direction for its domain while collaborating across clinical development, translational research, and regulatory functions.</p><p></p><p>
Beyond hands-on design and delivery, the position carries accountability for agent evaluation frameworks (reliability, hallucination risk, auditability), agentic governance, stakeholder coordination across globally dispersed teams, and external visibility through publications and conference presentations. Where a team is in scope, the leader is expected to coach and develop data scientists and AI engineers at the frontier of applied AI in pharma. It requires 10+ years of production AI/ML experience with specific fluency in agentic design patterns and responsible-AI practices.</p><p></p><p><b>
 Major Accountabilities:</b></p><p></p><ul><li>
Develop and execute a roadmap for agentic AI systems &mdash; including multi-agent architectures, tool-using LLMs, and autonomous workflow orchestration &mdash; across multiple business verticals</li><li>
Architect, prototype, and productionize agentic pipelines: agent orchestration, memory and context management, tool integration, and human-in-the-loop governance frameworks</li><li>
Define agent evaluation frameworks covering reliability, hallucination risk, task completion rate, and regulatory-grade auditability</li><li>
Design and implement the data foundations (master data, governance, quality) that agentic systems depend on for grounded, trustworthy decision-making</li><li>
Identify and integrate internal/external data sources, APIs, and knowledge bases as agent-accessible tools with appropriate access controls and governance</li><li>
Strategically coordinate and prioritize team resources across initiatives; proactively manage risks, stakeholder expectations, and competing priorities</li><li>
Collaborate with globally dispersed stakeholders, external partners, and cross-functional teams to translate business problems into agentic AI solutions</li><li>
Proactively evaluate the evolving agentic AI landscape (e.g., reasoning models, agent frameworks, MCP, RAG) and guide technology selection</li><li>
Provide agile consulting and guidance on unplanned, high-priority analytical and AI challenges</li><li>
Publish and present at conferences and academic institutions; serve as a Novartis ambassador for agentic and applied AI</li><li>
Coach and develop junior data scientists and AI engineers in agentic design patterns and responsible AI practices</li></ul><p></p><p><b>
Key Performance Indicators:</b></p><p></p><ul><li>
Agentic system deployment rate and measurable business impact per vertical</li><li>
Agent reliability and task-completion metrics vs. baseline</li><li>
Governance and compliance endorsement at program tollgates</li><li>
Successful implementation against enterprise data and AI program objectives</li></ul><p></p><p><b>
Minimum Requirement: Work Experience:</b></p><p></p><ul><li>
Advanced degree in related field preferred. 10+ years in Data Science or AI, with demonstrable experience building and deploying production AI/ML systems</li><li>
Hands-on experience with agentic frameworks (e.g., LangGraph, AutoGen, CrewAI, or equivalent)</li></ul><p></p><p><b>
Skills:</b></p><p></p><ul><li>
Agentic AI system design and orchestration</li><li>
LLM tool-use, RAG, and multi-agent coordination patterns</li><li>
AI governance and responsible AI (EU AI Act awareness a plus)</li><li>
Machine learning, deep learning, NLP and GenAI</li><li>
Data governance, quality, and strategy</li><li>
Statistical analysis and data visualization</li><li>
Change management and organizational awareness</li><li>
Stakeholder engagement and business value creation</li><li>
Mentorship and learning agility</li></ul><p></p><p><b>
Language:</b></p><p></p><ul><li>
English</li></ul><p></p><p><b>
Rewards</b></p><p>
At Novartis, we&rsquo;re committed to reimagining medicine together - and rewarding the people who make it happen.</p><p></p><p>
The rewards of being part of our team go far beyond base pay and incentives. We also offer a variety of competitive benefits in kind to help you thrive personally and professionally, such as insurance plans, retirement plans, wellbeing resources and global recognition programs. In addition, we provide flexible and hybrid working options, where possible, and a minimum of 14 weeks paid parental leave.</p><p></p><p>
Expected Annual Base Salary Range for role:</p><ul><li>
London: 100,240.00 - 143,200.00 - 186,160.00 GBP Annual</li></ul><p></p><p>
The salary offered is determined based on gender-neutral objectives, such as relevant skills, competencies and experience in accordance with the Novartis pay setting policy and upon joining Novartis will be reviewed periodically.
</p><p></p><p>In addition to your base salary, you may be eligible for a performance-based bonus depending on certain performance parameters. Further details will be provided during the application process.
</p><p></p><p>Pay equity is a fundamental principle of our employment policy and reflects our commitment to create a diverse, equitable and inclusive environment that treats all employees with dignity and respect, as outlined in our Code of Ethics.</p><p></p><p>
Read our brochure to learn more about our global total rewards offering: https://www.novartis.com/sites/novartis_com/files/novartis-life-handbook.pdf
</p><p><i>Note: Benefits and compensation may vary by country and are subject to local legal requirements, including provisions of collective bargaining agreements where applicable. A full overview of your compensation package, including any relevant collective bargaining agreement details applicable to your role based on your employment location and Novartis employer entity, will be communicated separately to you during the application process.</i>
</p><p></p><p><b>Commitment to Diversity and Inclusion / EEO paragraph:</b></p><p>
Novartis is committed to building an outstanding, inclusive work environment and diverse teams&rsquo; representative of the patients and communities we serve.</p><p></p><p><b>
Why Novartis:</b> Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients&rsquo; lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture</p><p><b>
Benefits and Rewards: </b>Read our handbook to learn about all the ways we&rsquo;ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards
</p></div></div><div><div><p><b>Why Novartis:</b> Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients&rsquo; lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture</p><p><b>
Benefits and Rewards:</b> Learn about all the ways we&rsquo;ll help you thrive personally and professionally.<br>
Read our handbook (PDF 30 MB)</p></div></div></div>
<br><div><div>Primary location salary range
<div>&pound;100,240.00 - &pound;186,160.00
</div></div><div>Division
<div>Development
</div></div><div>Business Unit
<div>Development
</div></div><div>Location
<div>United Kingdom
</div></div><div>Site
<div>London (The Westworks)
</div></div><div>Company / Legal Entity
<div>GB16 (FCRS = GB016) Novartis Pharmaceuticals UK Ltd.
</div></div><div>Functional Area
<div>Data and Digital
</div></div><div>Job Type
<div>Full time
</div></div><div>Employment Type
<div>Regular
</div></div><div>Shift Work
<div>No</div></div></div><div></div>

Director Data Science & Agentic AI

Houseful

<div><p>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.</p><p>
</p><p><b>The Role</b></p><p>
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.</p><p>
</p><p><b>What You&rsquo;ll Do</b></p><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><p>
</p><p><b>Who You Are</b></p><ul><li><b>A Builder: </b>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><b>Commercially Sharp: </b>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><b>A Technical Authority: </b>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><b>Cross-Functionally Effective: </b>You move comfortably between engineering, commercial, and operational stakeholders, translating between data science and business outcomes without losing either audience.</li><li><b>Outcome-Focused: </b>You prioritise ruthlessly, track ROI on your work, and resist the pull of interesting-but-unactionable projects.</li><li><b>Comfortable in Ambiguity: </b>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><p>
</p><p><b>Our Technology Stack</b></p><p>
<b>Languages</b></p><ul><li>Python, SQL</li></ul><p><b>
BI &amp; Reporting</b></p><ul><li>ThoughtSpot</li></ul><p><b>
Platform</b></p><ul><li>Mission Control (Alto&rsquo;s internal data platform)</li></ul><p><b>
AI / ML</b></p><ul><li>Modern ML frameworks; experimentation and causal inference tooling; LLMs and practical AI applications</li></ul><p>
</p><p><b>Why Join Alto?</b></p><p>
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.</p><b><br>
Benefits</b><ul><li><br>
<b>Hybrid &mdash; 2 days/week in London HQ</b></li><li><b>Everyday Flex</b> &mdash; greater flexibility over where and when you work</li><li><b>25 days annual leave</b> &mdash; plus extra days for years of service</li><li><b>Day off for volunteering &amp; Digital detox day</b></li><li><b>Festive Closure</b> &mdash; business closed between Christmas and New Year</li><li><b>Cycle to work and electric car schemes</b></li><li><b>Free Calm App membership</b></li><li><b>Enhanced Parental leave</b></li><li><b>Fertility Treatment Financial Support</b></li><li><b>Group Income Protection &amp; private medical</b></li><li><b>Gym on-site in London</b></li><li><b>7.5% pension contribution by company</b></li><li><b>Discretionary annual bonus up to 10%</b> &mdash; of base salary</li><li><b>Talent referral bonus up to &pound;5K</b></li></ul></div>

Data Science Lead

Fresha

<div><h4 class="jobSectionHeader"><b>The AI-powered OS for beauty, wellness and self-care</b></h4><p></p><p><b>
About Fresha</b><br>
<br>
Fresha is the AI-powered operating system for the global beauty, wellness and self-care industry, connecting and powering everything from salons and barbers to spas, medspas, fitness studios and health practices.<br>
<br>
Trusted by millions of consumers and businesses worldwide. Fresha is used by 140,000+ businesses and 450,000+ stylists and professionals worldwide, processing over 1 billion appointments to date.<br>
<br>
The company is headquartered in London, United Kingdom, with 15 global offices located across North America, EMEA and APAC.</p><div><p>
Fresha allows consumers to discover, book and pay for beauty and wellness appointments with local businesses via its marketplace, while beauty and wellness businesses and professionals use an all-in-one platform to manage their entire operations with an intuitive business software and financial technology solutions.</p></div><p></p><div><p>
Fresha&rsquo;s ecosystem gives merchants everything they need to run their business seamlessly by facilitating appointment bookings, point-of-sale, customer records management, marketing automation, loyalty, beauty products inventory and team management.</p></div><p></p><div><p>
The consumer marketplace unlocks revenue potential for partner businesses by leveraging the power of online bookings and automated marketing through mobile apps and advanced integrations with major tech brands including Instagram, Facebook and Google.</p></div><p></p><div><div><div><div><div><div><div><div><div><p>
We process millions of transactions and generate rich behavioural data across consumers and partners. Despite this, data science is still early at Fresha. That's the opportunity.</p></div></div></div></div><p></p><p><b>
About the Role</b></p><p>
We're hiring a Head of Data Science to build DS into a core function at Fresha, not manage what already exists. Today the team is small but technically strong. We have production ML models in fraud detection, text moderation, and taxonomy classification, running on SageMaker with a dbt/Snowflake data stack. But we're operating reactively, and we know there's significantly more value DS can unlock across the marketplace.</p><div><div><div><div><p>
You'll have a clear mandate, leadership buy-in, and a technically strong team already in place. Your job is to set the direction, grow the team, and make data science visible and indispensable to how Fresha makes decisions and builds products.</p><p>
This role is right for you if you've done this before - taken a small DS team at a scaling company and turned it into something the business can't operate without.</p><p>
To foster a collaborative environment that thrives on face-to-face interactions and teamwork, this role will be based in our dog-friendly office 5 days per week in London: The Bower, 207-122, Old Street, London EC1V 9NR.</p></div></div><p></p><div><p><b>
What You'll Do</b></p></div></div></div></div><div><p><b>
Strategy &amp; Influence</b></p><ul><li><p>
Define the DS roadmap and align it to Fresha's business priorities across marketplace, payments, and partner growth</p></li><li><p>
Shift DS from reactive (responding to product requests) to proactive (identifying opportunities, building POCs, running demos)</p></li><li><p>
Build DS credibility with leadership - make the function visible, understood, and sought out</p></li><li><p>
Partner with Product, Engineering, and Commercial teams to embed DS into decisions</p></li></ul><div><p><b>
Delivery &amp; Technical Leadership</b></p><ul><li><p>
Ship ML products that drive measurable business impact - not just models, but outcomes</p></li><li><p>
Establish experimentation as a discipline: A/B testing infrastructure, causal inference, automated experimentation for optimisations</p></li><li><p>
Build foundational DS infrastructure: feature store, model governance, monitoring, CI/CD for ML</p></li><li><p>
Stay hands-on enough to evaluate technical decisions and architecture trade-offs</p></li><li><p>
Contribute directly to high-impact projects when needed</p></li></ul><p><b>
Visibility &amp; Advocacy</b></p><ul><li><p>
Champion DS internally through demos, stakeholder education, and proactive engagement with PMs</p></li><li><p>
Drive external visibility: engineering blog posts, conference talks, thought leadership</p></li><li><p>
Help Fresha attract top DS talent by making the function known</p></li></ul><p><b>
Team Building</b></p><ul><li><p>
Scale the team in line with what the roadmap demands - hiring across ML engineering, data science, and MLOps</p></li><li><p>
Develop the existing team, create career paths, and set technical and cultural standards</p></li></ul></div></div></div></div></div></div><p></p><p><b>
What the First Year Looks Like</b><br>
3 months: DS roadmap defined cross-functionally and signed off. New high-impact use cases on the table that the business hadn't previously identified. First POCs or MVPs in flight. DS is visibly present in product planning &mdash; already shifting from reactive to proactive.</p><p>
6 months: Multiple ML/AI use cases shipped or in live evaluation. Experimentation is active in at least one product area. DS achievements are visible internally - demos, showcases, early external presence.</p><p>
12 months: DS is a recognised, embedded function with a track record of delivery. Experimentation is a working discipline used beyond DS. MLOps maturity has stepped up. The team has grown in line with what was needed to get here.</p><p></p><p><b>
What You Bring</b></p><p><b>
Must-Haves</b></p><ul><li><p>
4-5 years in data science, ML engineering, or related technical fields</p></li><li><p>
3+ years directly managing and growing DS teams</p></li><li><p>
Track record of building a DS function - not just inheriting one. You've taken a team from small to meaningful and made DS matter to the business</p></li><li><p>
Shipped ML models to production at scale with real business outcomes</p></li><li><p>
Strong stakeholder management - comfortable influencing C-suite, product leaders, and commercial teams</p></li><li><p>
Technical depth to evaluate architecture decisions, review work, and call the right trade-offs</p></li><li><p>
Experience developing people - grown ICs into leads, created career ladders, built team culture</p></li></ul><p><b>
Nice-to-Haves</b></p><ul><li><p>
Experience in the marketplace, SaaS, or fintech businesses</p></li><li><p>
Familiarity with our stack: SageMaker, Snowflake, dbt, Docker</p></li><li><p>
Built or contributed to feature store, MLOps, or experimentation platform infrastructure</p></li><li><p>
Experience in establishing experimentation and A/B testing as an organisational practice</p></li><li><p>
Thought leadership - blog posts, talks, open-source contributions</p></li><li><p>
Experience making DS a &quot;core function&quot; at a company where it previously wasn't</p></li></ul><p></p><p><b>
Why This Role</b></p><ul><li><p><b>
Real data, real scale.</b> Millions of transactions, 120+ countries, rich behavioural signals across a two-sided marketplace. The data is there, and there's significantly more value to unlock.</p></li><li><p><b>
Strong technical foundation.</b> You're not starting from zero. There's a production ML stack, a team with deep context across the data and business, and working models in production. You're accelerating, not bootstrapping.</p></li><li><p><b>
Visible impact.</b> At Fresha's stage, DS improvements flow directly to business metrics. This isn't optimising the fifth decimal place - it's building capabilities that don't exist yet.</p></li></ul><p></p><p><b>
Interview Process</b></p><ul><li><p><b>
Screen Stage </b>- Video-call with a member from the Talent Team (30mins)</p></li><li><p><b>
1st Stage</b> - Google Hangout - soft skills &amp; technical skills (60 mins)</p></li><li><p><b>
2nd Stage</b> - In-person case study + live review with Team (60 minutes)</p></li><li><p><b>
Final Stage -</b> Stakeholder interview with Deputy Chief Product Officer OR Chief Technology Officer (60min)</p></li></ul><p></p><div><p><i>
We aim to finalise the entire interview process and deliver feedback within 4 weeks.</i></p></div><p></p><div><p>
Every job application received is reviewed manually by our talent team. While we strive to assess applications within 7 days, the sheer volume of talented individuals expressing interest may occasionally extend this timeframe.</p></div><p></p><p><b>
Inclusive workforce</b></p><p></p><div><p>
At Fresha, we are creating a culture where individuals of all backgrounds feel comfortable.</p></div><p></p><div><p>
We want all Fresha people to feel included and truly empowered to contribute fully to our vision and goals. Everyone who applies will receive fair consideration for employment.</p></div><p></p><div><p>
We do not discriminate based on race, colour, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability, or any other applicable legally protected characteristics in the location in which the candidate is applying.</p></div><p></p><div><p>
If you have any accessibility requirements that would make you more comfortable during the interview process and/or once you join, please let us know so that we can support you.</p></div></div>

Head of Data Science

WPP Media

<div><div><p><b>About WPP Media</b></p>
<p>
WPP is the trusted growth partner for the world's leading brands. With exceptional talent, trusted data and intelligence, and world-class partnerships &ndash; all united by our pioneering agentic marketing platform, WPP Open &ndash; we help clients navigate change, capture opportunity, and deliver transformational growth.</p>
<p>
WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working.</p>
<p>
For more information, visit wppmedia.com.</p></div><p><b>
Associate Director, Analytics &ndash; Global Clients</b></p>
<p>
This role is within the Data, Tech, and Analytics (DTA) team, within the Global Client Solutions organisation. The Global Client Solutions (GCS) team is responsible for all global clients within WPP. DTA is responsible for servicing clients with best-in-class data solutions, data strategy, analytics, technology and AI solutions to drive client growth. 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. We believe the best work happens when we're together, fostering creativity, collaboration, and connection.</p>
<p><b>
Who We Are Looking For</b></p>
<p>
We are seeking an Analytics Associate Director to join our growing Analytics &amp; Data Science team, reporting into the Data Tech and Analytics global lead. The team focuses on media effectiveness measurement, campaign analysis and client communication to help make brands become more valuable to the world.<br>
<br>
You will be working with a leading advertiser, JLR, to harness their data and improve the performance of their campaigns, developing and deploying media measurement solutions. Communication with client stakeholders and effective management of assigned tasks is critical in this role. You will be joining an award winning team, with more than 16 tech and media industry awards to our name, including Campaign Magazine's Tech Awards Agency of the Year, Best Use of AI, and Breakthrough Tech as Part of a Campaign awards.<br>
<br>
We have invested in giving you the tools to make you as successful as possible, including training/development, full access to Google Cloud Platform and a wider global community of analysts and data scientists.<br>
<br>
<b>Some of the things we'd like you to do</b></p><br>
<p><b>
Strategic Analytics Application:</b> Build and apply a deep understanding of marketing objectives to support Account teams with comprehensive measurement and testing plans. To help deliver &quot;best in class&quot; analytical capabilities across the agency with the wider Analytics team, including the use of new methods, techniques, tools and systems. Managing the process through to delivery and taking ownership of global roll out.</p>
<p><b>
Marketing &amp; Business Effectiveness: </b>Lead the creation of clear, robust and thought-provoking campaign reviews and insights, and show the wider team/clients how to improve effectiveness. Deliver insightful campaign reviews with actionable recommendations to improve marketing effectiveness.</p>
<p><b>
Measurement frameworks &amp; Experimentation:</b> Develop deep understanding of marketing platform testing and targeting abilities, and act in a consultative capacity in their implementation. Provide actionable insights and design experiments to optimise campaign performance - focusing on brand and conversion lift studies.</p>
<p><b>
Client Stakeholder Engagement:</b> Build trusted relationships with senior client marketing, analytics, and data leads, acting as a knowledgeable and credible day-to-day strategic partner.</p>
<p><b>
Internal Stakeholder Engagement:</b> Manage relationships with data engineering teams and set automation strategies to integrate new tools and solutions.</p>
<p><b>
Commercial Contribution:</b> Support the commercial health of your client account by contributing to the scoping and delivery of high-value analytics projects. Participate in new business pitches, helping to develop data and tech solutions that demonstrate the value of WPP Media's capabilities. Coordinate with third-party vendors for the assessment and management of bespoke measurement solutions, including contracts and SOWs.</p>
<p><b>
Thought Leaderhsip:</b> Translate complex data concepts for stakeholders and contribute to the company's data strategy, promoting data-driven innovation within the media industry.</p>
<p><b>
Skills &amp; Qualifications</b></p>
<p>
At WPP Media, we believe in the power of our culture and our people. It's what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP &amp; WPP Media's shared core values:</p>
<ul>
<li>You will be highly numerate: able to confidently interpret data and apply statistical tests to draw robust conclusions. Holding a degree(s) in a quantitative field: Statistics, Mathematics, Economics, Engineering, Physical Science or Computer Science</li>
<li>Experience in analytics, measurement, data science, or a related field</li>
<li>Knowledge of applying measurement to media campaigns through Meta/Google, through brand and conversion lift studies, matched market tests or otherwise</li>
<li>Well-developed problem-solving skills and the ability to think critically and creatively</li>
<li>Strong understanding of statistics including hypothesis testing, descriptive statistics and distribution theory</li>
<li>Strong communication skills, with the ability to present complex ideas to both technical and non-technical audiences</li>
<li>Able to work independently and as part of a cross-functional team, using project management tools such as Jira/Trello. Ability to project manage analytics projects.</li>
<li>Highly capable at presenting data in a visually engaging and insightful manner that cuts through the noise</li>
<li>Experience in mentorship and management, ability to display empathy in difficult situations and lead by example</li>
<li>Stay up-to-date with the latest industry trends and advancements in data science and analytics</li>
<li>Proficiency in SQL &amp; R/Python, including understanding of packages such as pandas, numpy, scipy &amp; matplotlib.</li>
<li>Strong understanding of what data points can be collected and analysed in a digital campaign, and how each data point should be analysed. Including knowledge of media data and incremental measurement, including both Direct Response and Brand campaigns</li>
</ul><ul><li>Working knowledge of advanced measurement tools including MMM, MTA, Sales Lift, and Brand Studies.</li></ul><br>
<p></p>
<p>
#LI-Promoted</p><p></p><div>
<p>
Please read our Privacy Notice for more information on how we process the information you provide.</p></div></div>

Associate Director, Analytics - Global Clients

International Swaps and Derivatives Association

<div><div><p>June 30, 2026</p>
<p><b>Job Title:</b> Assistant Director, Artificial Intelligence</p>
<p><b>Reports to:</b> Senior Director, Digital Transformation, Analytics</p>
<p><b>Location:</b> London</p>
</div><div><p><b>Job purpose</b><br>
This is a hands-on role. The successful candidate will architect and build production AI systems directly, while owning delivery, quality, evaluation, and partner management across the AI Solutions Lab portfolio. The role reports to the Senior Director of Digital Transformation and head of the AI Solutions Lab.</p><br>
<p></p>
<p><b>
Duties and responsibilities</b></p>
<ul>
<li>Deliver the next phase of the ISDA AI Solutions Lab&rsquo;s buildout, helping move current AI initiatives from prototype/MVP stage toward robust, scalable and member-ready delivery. Architect and build the next phase of AI agents, external and internal.</li>
<li>Own the design and delivery of AI solutions that make ISDA standards and digital solutions more accessible, usable and AI-ready for members.</li>
<li>Help shape and scale the ISDA Knowledge Base and Assistant as the governed foundation for AI-enabled access to ISDA standards, taxonomies and related IP.</li>
<li>Oversee enhancement of priority AI capabilities including the CDM Coder, DRR Translator, Tracer, cross-jurisdiction analysis and AI legal opinions initiatives.</li>
<li>Help drive development and rollout of internal AI capabilities and agents aligned with the internal AI deployment roadmap.</li>
<li>Define product requirements, broader Agents orchestration, architecture direction, evaluation harnesses and quality standards and delivery priorities across the AI Solutions Lab portfolio.</li>
<li>Work closely with internal SMEs across CDM, DRR, legal, IT and product teams to ensure solutions are accurate, grounded and useful in real workflows.</li>
<li>Reach out to members for pulse checks and convert member and stakeholder feedback into roadmap decisions, product refinements and delivery choices to maximize adoption.</li>
<li>Help define practical connectivity and delivery models, including MCP servers and packaged AI Skills, so members can consume ISDA AI capabilities safely within their own environments.</li>
<li>Contribute to broader ISDA AI strategy development, including alignment between external member-facing AI solutions and internal AI deployment priorities.</li>
<li>Lead AI quality, guardrails and governance across the Lab&rsquo;s solutions, including evaluation harnesses, groundedness and traceability checks, observability and tracing, confidence frameworks, security and safe use boundaries, both internally and externally.</li>
<li>Own cost aware design of AI workloads, balancing performance and reliability against inference and infrastructure spend.</li>
<li>Manage relevant external partners and specialist vendors, ensuring work is aligned to ISDA&rsquo;s priorities, timelines, architecture and ownership model.</li>
<li>Support the Senior Director including for executive and board reporting by articulating progress, key risks, delivery needs and strategic value in a clear and concise way.</li>
<li>Help build a durable internal AI capability for ISDA that protects ISDA IP, accelerates adoption of ISDA standards and reinforces ISDA&rsquo;s strategic position in the market<b><i>.</i></b></li></ul><br>
<p></p>
<p><b>
Relevant Skills / Abilities</b></p>
<ul>
<li>Strong senior-level experience (at least five years) leading the design and delivery of AI-enabled products or platforms from prototype through controlled rollout and production, with a demonstrable track record of shipping production AI systems that serve real users.</li>
<li>Hands-on engineering ability in Python (and ideally TypeScript/React for front end UI) and Java, and comfortable building production systems directly.</li>
<li>Deep understanding of LLMs, retrieval-augmented generation (including hybrid retrieval across semantic, graph and keyword search, with reranking and embedding-model selection), knowledge bases, knowledge graphs and ontologies, agentic workflows and skills, evaluation methods (eval harnesses, LLM-as-judge, groundedness and faithfulness metrics, tracing), and model risk controls.</li>
<li>Experience building secure, scalable and reliable AI solutions in enterprise environments, including governance, permissions, auditability and data protection including private retrieval architectures and ensuring proprietary data is not exposed to external model providers</li>
<li>Hands-on AWS experience (Bedrock, Neptune, OpenSearch, Lambda) is very important. Strong engineers able to ramp quickly will also be considered. Cost-aware design of inference and infrastructure spend is expected.</li>
<li>Proven ability to translate complex domain knowledge into usable AI products, ideally in financial markets, regulatory technology, legal tech, standards or data-intensive environments; or a demonstrated ability to ramp quickly on a complex domain.</li>
<li>Strong product and solution architecture skills, with the ability to define use cases, prioritize roadmap items and align technical delivery with strategic business outcomes.</li>
<li>Experience overseeing external vendors, technology partners and proof-of-concept work, while retaining internal control of direction, quality and IP.</li>
<li>Ability to work closely with subject matter experts to refine AI tools iteratively and turn specialist feedback into practical product improvements.</li>
<li>Strong grasp of structured data, taxonomies, ontology-style data models and mappings across complex standards or schemas.</li>
<li>Experience with user testing, controlled pilots, adoption planning, training and feedback loops for specialist user populations.</li>
<li>Strong judgment on AI risks, including hallucination, groundedness, security, explainability, confidence scoring and safe deployment boundaries.</li>
<li>Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related discipline, or equivalent practical experience, is desirable.</li>
<li>Excellent communication skills, including the ability to understand member issues, to work across the organization and influence and align stakeholders, and to brief senior management and explain technical issues in concise business language.</li>
<li>Demonstrated ability to operate in a lean, hands-on environment, balancing strategy, execution and stakeholder engagement.</li></ul></div></div><p></p>

Assistant Director, Artificial Intelligence, London

Explore 805+ Data science director in London this July. Find roles across top companies and apply now to boost your career.