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senior machine learning engineer Jobs in London

senior machine learning engineer

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machine learning manager

Monzo

<div><div>We're on a mission to make money work for everyone.

We're waving goodbye to the complicated and confusing ways of traditional banking.

After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts, accounts for 16-17 year olds, a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save, invest and combine their pensions with us.

With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers!

We're not about selling products - we want to solve problems and change lives through Monzo ❤️</div><h4 class="jobSectionHeader"> 
London/Cardiff/UK Remote | &pound;138,000 to &pound;176,000 + Incentive Awards tied to your performance + benefits | Hear from the team ✨</h4>
<h4 class="jobSectionHeader">About the role</h4>

Borrowing is one of Monzo's most important growth engines. We've built strong scale in the UK, and the next phase is even more ambitious: grow in the UK, expand into new customer segments, and build the underwriting capability needed to scale into Europe.

We're looking for a senior ML leader to help shape that next phase.

You'll lead a high-calibre team of ML scientists and help define Borrowing's ML roadmap across UK growth, new customer segments, and EU expansion. You'll work across underwriting, pricing, limits, and lifecycle decisioning &mdash; improving today's models while helping build the next generation of capability for Monzo.

This role combines near-term commercial impact with long-term strategic advantage:
<ul>
<li>improving performance across our range of products</li>
<li>unlocking new data and faster model development</li>
<li>helping Monzo build underwriting that scales into new markets</li>
<li>shaping how advanced ML and AI can create real value in Borrowing</li>
</ul>
You'll partner closely with leaders across Credit Strategy, Product, Engineering, Model Validation, Data, and Platform, and influence decisions that shape both business performance and the long-term architecture of credit decisioning at Monzo.
<h4 class="jobSectionHeader">
What you'll own</h4>
<ul><li>Borrowing ML roadmaps across UK optimisation, new customer segments, and EU expansion</li>
<li>Faster model improvement through new data and feature engineering</li>
<li>How Monzo uses Open Banking, transaction intelligence, and external data in credit decisioning</li>
<li>More portable underwriting capabilities across products, customer segments, and markets</li>
<li>Hiring, leading, and developing a high-performing ML team</li>
<li>Raising the bar on model quality, governance, tooling, and speed of iteration</li>
</ul><h4 class="jobSectionHeader">What you'll be working on</h4>

Examples of the challenges you could help lead:
<ul>
<li>Improving underwriting models across Loans, Flex, and Overdrafts</li>
<li>Expand the data we use in our models</li>
<li>Building better feature engineering and model shipping capability</li>
<li>Improving transaction intelligence for credit use cases</li>
<li>Developing underwriting capabilities for new customer segments and EU markets</li>
<li>Shaping Monzo's approach to advanced ML and AI</li>
</ul><h4 class="jobSectionHeader">Our technology stack</h4>

We rely heavily on the following tools and technologies, although we do not expect applicants to have prior experience of all of them:
<ul>
<li>Google Cloud Platform</li>
<li>BigQuery SQL and dbt</li>
<li>Python and the PyData stack</li>
<li>Google AI Platform</li>
<li>AWS</li>
<li>Python for ML services</li>
<li>Go for backend services</li>
<li>AI tooling for productivity</li>
<li>Google Workspace including Gemini</li>
<li>ChatGPT Enterprise</li>
<li>Claude Code</li>
</ul><h4 class="jobSectionHeader">You should apply if</h4>
<ul><li>You want to shape the next phase of credit decisioning at one of Europe's most ambitious fintechs</li>
<li>You enjoy combining strategic leadership with strong technical judgment</li>
<li>You're excited by the intersection of underwriting, data, product, and platform capability</li>
<li>You like building teams as much as building models</li>
<li>You care about real customer and business impact</li>
</ul><h4 class="jobSectionHeader">You must have</h4>
<h4 class="jobSectionHeader">Credit and machine learning</h4>
<ul><li>Strong knowledge of machine learning, statistics, and decisioning systems</li>
<li>Deep experience in credit risk and lending</li>
<li>Experience building, deploying, and iterating credit models in production</li>
<li>Experience pushing the innovation frontiers of the credit industry</li>
</ul><h4 class="jobSectionHeader">Leadership and delivery</h4>
<ul><li>Experience leading and developing senior ML scientists</li>
<li>Strong cross-functional leadership with Product, Credit Strategy, Engineering, and Validation</li>
<li>Track record of turning strategy into practical delivery in a regulated environment</li>
</ul><h4 class="jobSectionHeader">It would be great if you also have</h4>
<ul><li>Experience across more than one market</li>
<li>Experience with advanced ML methods and AI on structured financial data</li>
</ul><h4 class="jobSectionHeader">The interview process</h4>
<ul><li>30 min Recruiter Call</li>
<li>45 min Initial Call</li>
<li>60 min ML technical interview</li>
<li>60 min People Leadership interview</li>
<li>60 min Product / Credit ML interview</li>
</ul>
All interviews will be conducted through Google Meet.
<h4 class="jobSectionHeader">
What's in it for you</h4>

 &pound;138,000 to &pound;176,000 ➕ plus stock options &amp; benefits

✈️ We can help you relocate to the UK

✅ We can sponsor visas

This role can be based in our London office with a hybrid working pattern, or fully remote within the UK with occasional travel to London.

 We'll set you up to work from home, including support for remote setups.
<ul><li>We offer flexible working hours and trust you to work in a way that lets you do your best work.</li></ul>

 Learning budget for books, training courses and conferences

➕ And much more &mdash; see our full list of benefits here 
 
#LI-DC2 #LI-Remote<div>

Equal opportunities for everyone

Diversity and inclusion are a priority for us and we're making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we're embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog, 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report.

We're an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status.

If you have a preferred name, please use it to apply. We don't need full or birth names at application stage</div></div>

Senior Machine Learning Manager, Borrowing

Compare The Market

<div>Machine Learning Engineering Manager
Function: Data &amp; AI Solutions 
Location: Hybrid, London office 
Curious about what&rsquo;s next? 
So are we. Join Compare the Market and help to make financial decision making a breeze for millions.
At Compare the Market, we&rsquo;re a purpose-driven business powered by tech and AI. We&rsquo;re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.
We&rsquo;ve carved a meerkat-shaped niche and we&rsquo;re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you&rsquo;ll fit right in. 
We&rsquo;d love you to be part of our journey.
Compare the Market is at an inflection point. We are shifting from a business that answers data questions to one that builds the intelligence powering our AI systems and platform.
As a Machine Learning Engineering Manager in our Data &amp; AI Solutions team, you will lead a team building and owning production systems at the heart of our AI platform. That means real-time inference APIs serving millions of customers, batch data products powering intelligent decision-making, and LLM-based agentic solutions spanning both customer-facing products and internal tools that shape how the wider team works. These are not simple systems - and building them well, keeping them healthy, and continuously raising the engineering bar is what this team exists to do.
You will set technical direction, develop your team, and work closely with data, product, commercial and engineering colleagues to ensure the intelligence your team builds has a real effect on the business. 
Some of the great things you'll be doing:
Leading Delivery of ML and AI Systems<ul><li>
Lead and develop a team of ML engineers, creating the conditions for them to deliver robust, scalable systems into production - spanning real-time inference APIs, batch data products, and LLM-based agentic solutions</li><li>
Collaborate closely with data scientists to move prototypes into high-quality production systems, maintaining quality and performance as complexity scales</li><li>
Drive team planning, estimation, and sprint delivery - ensuring projects are delivered on time and to a high standard</li><li>
Ensure every system your team ships connects to a real outcome and has a mechanism to improve over time</li></ul> 
Growing Your Team<ul><li>
Develop your team of machine learning engineers through regular feedback, technical mentorship and honest career conversations</li><li>
Contribute to hiring, helping bring in people who combine technical rigour with curiosity and commercial awareness</li><li>
Foster a team environment where ambition and delivery reinforce each other</li><li>
Contribute to standards and practices across the wider Data &amp; AI Solutions chapter</li></ul> 
Technical Leadership<ul><li>
Set the standard for ML and AI engineering quality, reproducibility, and production-readiness across your team - covering model pipelines, deployment tooling, system design, and lifecycle automation</li><li>
Take ownership of how the team approaches production health: knowing when a system is degrading, having a plan to address it, and ensuring monitoring and observability are built in from the start</li><li>
Contribute to the design and evolution of our ML and AI tooling and shared platform components</li><li>
Be hands-on in design sessions, code reviews, and architectural decisions where your input matters</li><li>
Guide your team through a fast-moving tooling landscape spanning classical ML, LLM-based systems, and agentic AI patterns - knowing when each is the right approach</li><li>
Champion responsible, auditable AI - particularly important in a regulated financial services environment where precision and explainability are non-negotiable</li><li>
Encourage and model the use of AI-assisted development tools within your team, and be actively curious about how automated coding and workflow tools can increase the pace and quality of your team's output</li></ul> 
Stakeholder Partnership<ul><li>
Work closely with data, product, commercial and engineering leads to translate strategic priorities into well-scoped work</li><li>
Represent your team's work and capability to senior stakeholders, building confidence in what the team delivers and how it operates</li><li>
Help shape platform direction by feeding back requirements from applied ML delivery</li></ul> 
What we'd like to see from you:
The Essentials<ul><li>
Experience leading engineering teams focused on machine learning, ML platforms and AI systems</li><li>
Proven track record deploying and managing ML and AI systems in production at scale - including real-time inference, batch data products, and LLM-based solutions</li><li>
Strong Python and ML and AI engineering fundamentals - sufficient to assess your team's work and contribute directly when needed</li><li>
Understanding of infrastructure-as-code and CI/CD for ML systems (e.g. Terraform, GitHub Actions, ArgoCD)</li><li>
Clear communication: able to make technical work legible to commercial and product audiences</li><li>
Experience working in agile environments with clear accountability to delivery</li><li>
A degree in a quantitative discipline, or equivalent experience with production ML and AI systems - we are interested in what you can do, not where you studied</li></ul> 
Highly Valued<ul><li>
Hands-on experience with LLM-based systems: prompt engineering, RAG, tool use, or orchestration frameworks such as LangGraph or LangChain</li><li>
Familiarity with multi-step AI patterns - building systems where models plan, retrieve information, and take sequences of actions</li><li>
Understanding of experimentation at scale and the infrastructure needed to run it well</li><li>
Experience building or managing internal ML platforms, experimentation frameworks, or feature stores</li><li>
Interest in responsible AI and model governance practices</li></ul> 
Why Compare the Market?
We&rsquo;re a business built for pace and performance. Here, you&rsquo;ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress.
We believe diverse teams make better decisions, and we&rsquo;re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive.
If you&rsquo;re ready to stretch yourself, raise the bar, and grow with a team that&rsquo;s serious about performance, innovation, and purpose, we&rsquo;d love to hear from you.</div>

Machine Learning Engineering Manager

Affirm

<div><div>Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.</div>
Join Affirm as a Machine Learning Engineering Manager and become a pivotal part of our Repayment &amp; Recovery machine learning group. Specifically, you will manage a team of ML engineers that builds the models powering the post-origination side of the credit lifecycle using novel ML techniques and rich representations of data to predict repayment behaviour, prioritise and personalise collections, and minimise loss after a loan is originated.

In this role, you will help shape the future of machine learning at Affirm. You'll partner with engineering, product, and risk leaders to design, implement, and scale advanced ML solutions that drive critical capabilities across the company. You will mentor engineers, bring clarity to complex, ambiguous problems, and contribute to a cohesive long-term ML strategy.

This role is based in Europe, with openness to candidates in the UK, Poland, or Spain.

What you'll do
<ul>
<li>Set the technical strategy for your team, and help your engineers tie it together with critical, business-impacting projects across repayment, collections, recovery, and loss mitigation.</li>
<li>Act as a force-multiplier through your definition and advocacy of technical solutions and operational processes.</li>
<li>Collaborate across teams in the product development lifecycle by partnering with product management, design, analytics, and risk to ensure technical sustainability, risks and trade-offs are well understood and managed.</li>
<li>Develop talent by providing feedback and guidance, and leading by example.</li>
</ul>
What We Look For
<ul>
<li>Bachelor's in a technical field with 8+ years of industry experience, including 3+ years managing engineers.</li>
<li>A background in financial services, specifically in credit / lending, with hands-on experience in post-origination modeling &mdash; collections, repayment, recovery, loss mitigation, early-warning or behavioural risk, or similar.</li>
<li>Proficiency in machine learning with experience in areas including tree-based models, transformers, deep learning, and agentic ML.</li>
<li>Strong engineering skills and the ability to provide hands-on technical leadership while working with our code and architecture.</li>
<li>You thrive in ambiguity, and are comfortable moving from low level language idioms all the way to the architecture of large systems to understand how they work.</li>
<li>This position requires either equivalent practical experience or a Bachelor's degree in a related field.</li>
</ul><h3 class="jobSectionHeader">Compensation &amp; Benefits</h3>

Base Pay Grade - P

Equity Grade - 7

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidised medical coverage, dental and vision for you and your dependents.)

Base pay range per year: &pound;142,000 - &pound;190,000

Location: UK Remote

 #LI-Remote<div><div> 

Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.

We're extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:
<ul>
<li>Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents</li>
<li>Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses</li>
<li>Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge</li>
<li>ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount</li>
</ul>
We believe It's On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.
</div>
<div>By clicking &quot;Submit Application,&quot; you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.</div></div></div>

Manager, Machine Learning Engineering (Repayment & Recovery)

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

Haystack

<div>
 We are working with a pioneering technology firm that is at the forefront of developing cutting-edge AI solutions for real-world applications across various industries. This company is renowned for its innovative approach to machine learning and its commitment to pushing the boundaries of what's possible.
 
 
 The Role
 
 
 <ul>
 <li>
 Develop, train, and optimise advanced computer vision and machine learning systems
 </li>
 <li>
 Deploy machine learning solutions in constrained edge environments
 </li>
 <li>
 Work with a team of experts on innovative AI projects
 </li>
 <li>
 Contribute to the full lifecycle of machine learning model development
 
 
 </li>
 </ul>
 What You'll Need
 
 
 <ul>
 <li>
 Proven experience as a Machine Learning Engineer
 </li>
 <li>
 Expertise in computer vision and machine learning model development
 </li>
 <li>
 Familiarity with deploying models in edge environments
 </li>
 <li>
 Strong problem-solving skills and an analytical mindset
 </li>
 <li>
 Excellent communication and collaboration abilities
 
 
 </li>
 </ul>
 What's On Offer
 
 
 <ul>
 <li>
 Competitive salary based on experience
 </li>
 <li>
 Opportunity to work on groundbreaking AI technology
 </li>
 <li>
 Diverse and inclusive work environment
 </li>
 <li>
 Professional growth and development opportunities
 
 
 </li>
 </ul>
 Apply via Haystack today!
 
 
</div>

Machine Learning Engineer

Sagacity

<div>
 
 As a Data Scientist within the Analytics Team, you will contribute to data-driven strategies for our clients. Working closely with the Data &amp; Analytics Manager and senior colleagues, you will deliver data science projects and collaborate with stakeholders across data strategy, sales, account management, delivery and marketing.
 
 
 
 
 
 You will bring solid technical skills and commercial awareness to deliver data solutions that drive measurable operational performance. This is a hands-on role - ideal for someone who thrives on translating data into actionable insight and producing high-quality outcomes.
 
 
 
 
 
 
 About the Role
 
 
 
 
 
 
 As a Data Scientist within the Analytics Team, you will contribute to data-driven strategies for our clients.
 
 
 
 
 
 
 Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Deliver data science projects, from problem definition through to actionable insights and presentation of results
 </li>
 <li>
 Develop and apply predictive modelling, supervised and unsupervised machine learning techniques to optimise client operations and business outcomes
 </li>
 <li>
 Build and maintain data pipelines, ensuring data quality, consistency, and integrity across multiple sources and formats
 </li>
 <li>
 Translate complex analyses into clear, commercially relevant recommendations for clients and internal stakeholders
 </li>
 <li>
 Work with client teams to identify analytical opportunities, support marketing strategy, and quantify the impact of data-driven decision-making
 </li>
 <li>
 Support pre-sales and client engagement, helping to demonstrate the value of data insight
 </li>
 <li>
 Follow best practices in data science, reproducible research, and ethical AI
 </li>
 <li>
 Collaborate cross-functionally to enhance the company&rsquo;s products and marketing data solutions
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 
 
 
 <ul>
 <li>
 2+ years&rsquo; experience in data science, analytics, or statistical modelling, ideally with commercial experience within the Telecoms, Banking or Utilities industries; or within a data-related consultancy
 </li>
 <li>
 Educated to degree level (postgraduate preferred) in a quantitative discipline such as Computer Science, Statistics, Mathematics, Economics, or similar
 </li>
 </ul>
 
 
 
 
 
 Required Skills
 
 
 
 
 
 <ul>
 <li>
 Working knowledge of statistical and machine learning methods (e.g. logistic regression, gradient boosting, random forests, clustering, NLP)
 </li>
 <li>
 Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering
 </li>
 <li>
 Strong command of SQL and familiarity with data engineering environments such as Databricks or similar
 </li>
 <li>
 Skilled in data visualisation and storytelling using tools such as Power BI, Tableau, Plotly, or Sigma
 </li>
 <li>
 Demonstrated ability to translate technical findings into strategic recommendations for non-technical audiences
 </li>
 <li>
 Commercially aware, with proven success in applying analytics to solve business problems
 </li>
 <li>
 Strong communicator; able to engage stakeholders and present findings with clarity and confidence
 </li>
 <li>
 Self-motivated, organised, and proactive, with the ability to manage multiple priorities and stakeholders in a fast-paced environment
 </li>
 <li>
 Willing to travel across the UK for client engagements
 </li>
 <li>
 Must have the right to work in the UK and a commitment to ongoing professional development
 </li>
 </ul>
 
 
 
 
 
 Preferred Skills
 
 
 
 
 
 <ul>
 <li>
 Regular iteration on our machine learning methodologies, tools, and frameworks
 </li>
 <li>
 Consistent demonstration of technical excellence and commercial insight in all project deliverables
 </li>
 <li>
 Measurable contribution to the enhancement of Sagacity&rsquo;s data science and analytics product suite
 </li>
 </ul>
</div>

Data Scientist

Data Idols

<div><h2 class="jobSectionHeader">Senior Data Scientist</h2>
<h3 class="jobSectionHeader">Salary: &pound;85K &ndash; &pound;95K</h3>
<h3 class="jobSectionHeader">Location: London (Hybrid &ndash; 3 days per week)</h3>

Data Idols are working with an ambitious early-stage technology company that is building a machine learning platform capable of solving complex behavioural prediction problems at scale.

Already working with paying customers and backed by experienced founders with a successful track record of building and exiting technology businesses, they&rsquo;re now looking for a Senior Data Scientist to own one of the most important parts of the company.
<h3 class="jobSectionHeader">
The Opportunity</h3>

This isn&rsquo;t a role where you&rsquo;ll optimise an existing model or become another specialist in a large data science team.

You&rsquo;ll be responsible for designing and building the machine learning capability at the heart of the business. Rather than creating a single predictive model, you&rsquo;ll develop automated systems capable of generating, deploying and continuously improving bespoke machine learning models for every customer.

You&rsquo;ll work with large-scale behavioural event data, applying machine learning, feature engineering and experimentation to improve prediction accuracy and drive measurable customer outcomes.

Working alongside highly experienced founders and recognised experts in machine learning, you&rsquo;ll have the opportunity to influence product strategy, shape technical direction and establish best practices from day one.

This is a genuine ownership role where your work will have a direct impact on both the product and the future success of the business.
<h3 class="jobSectionHeader">
Skills &amp; Experience</h3>
<ul><li>Strong commercial experience building machine learning models in Python</li>
<li>Excellent understanding of predictive modelling, classification or propensity modelling</li>
<li>Experience with feature engineering, model evaluation and experimentation</li>
<li>Comfortable working across the full machine learning lifecycle</li>
<li>Experience working with cloud platforms and modern ML tooling</li>
<li>Curious and analytical mindset</li>
</ul>
If you&rsquo;re looking for a role where you&rsquo;ll solve genuinely difficult machine learning challenges, build something from the ground up and see the direct impact of your work, we&rsquo;d love to hear from you.
<h2 class="jobSectionHeader">
Senior Data Scientist</h2></div><div></div>

Senior Data Scientist

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