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Senior AI and Data Engineer

London (Hybrid, 2 days per week) | £80,000 to £90,000

This is an opportunity to join a business at a pivotal stage of its AI transformation. With strong executive sponsorship, a clear roadmap of projects, and equity on offer ahead of the next private equity cycle, you will deliver impactful AI solutions that are actively shaping how the organisation operates.

The Company

They are a well established professional services firm with a large and diverse client base, backed by private equity and investing heavily in data and AI. The business is undergoing a significant transformation, with multiple AI initiatives already scoped and ready for delivery. Working alongside a small, high impact team, you will be closely connected to senior stakeholders and have real influence over technical direction. Their focus is on embedding AI across core business functions to drive efficiency and insight.

The Role

You will take ownership of end to end AI product delivery, building production ready solutions that integrate with business systems and workflows.

• Design, build and deploy AI applications from concept through to production
• Develop LLM powered tools and agentic workflows to automate internal processes
• Deliver use cases such as AI generated reporting, commercial intelligence, and internal knowledge agents
• Integrate AI solutions into existing platforms and systems
• Contribute to Azure based data engineering, including pipelines and data modelling
• Work across multiple projects, shaping delivery and prioritising impact
• Collaborate closely with business stakeholders to scope and deliver solutions

Your Skills and Experience

• Strong commercial experience building production AI applications in a cloud environment
• Hands on expertise with LLMs, prompt engineering, and agent based workflows
• Data engineering capability, including ETL processes, orchestration, and working with large datasets
• Ability to design and deploy scalable, reliable systems
• Experience working with modern AI tooling and development workflows
• Strong communication skills with the ability to work directly with non technical stakeholders
• A proactive, hands on mindset with a focus on delivering outcomes

What They Offer

• High ownership role within a small, growing AI team
• Exposure to a wide range of AI initiatives with strong leadership backing
• Clear opportunity to shape the future direction of AI within the business

How to Apply

To find out more or apply, please submit your CV.

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Director of Performance Marketing

London, hybrid working. Base salary £150,000 – £200,000 plus equity and benefits.

This is a rare opportunity to build the growth engine of a fast-scaling consumer fintech. You will take a strong performance marketing foundation and turn it into a differentiated advantage, shaping how millions of customers discover, join, and grow with a leading digital product.

The Company
They are a high-growth, app-led consumer financial services business on a mission to redefine how people engage with their money. With a multi-product ecosystem and a rapidly expanding customer base, data, AI, and experimentation sit at the heart of their strategy. Marketing is seen as a strategic growth driver, with meaningful investment in brand, performance, customer analytics, and MarTech. You will join a modern, collaborative leadership team that is focused on sustainable, profitable growth.

The Role
As Director of Performance Marketing, you will:

• Own the long-term performance marketing strategy for profitable new customer growth.
• Lead channel investment strategy, planning, and budgeting across paid social, search, and app acquisition.
• Build and refine measurement frameworks, from attribution and incrementality to media mix and unit economics.
• Partner closely with Product, Data, Customer Analytics, and CRM to optimise the full funnel, from impression to in-app activation and value.
• Lead and develop the performance marketing function, including a high-performing team and agency partners.
• Embed a rigorous test-and-learn culture across channels, audiences, creative, and propositions.
• Champion the use of AI and advanced analytics to drive workflow efficiency, insight, and optimisation.
• Act as a senior thought partner to the executive team on growth opportunities, risk trade-offs, and performance forecasts.

Your Skills And Experience
You will be a strong fit if you have:

• Proven success in scaling acquisition for a consumer-focused digital business, such as fintech, subscription, marketplace, or app-led services.
• Deep hands-on understanding of performance channels, especially Meta, Google, and app store acquisition.
• Strong commercial mindset with experience managing large budgets and performance-driven investment decisions.
• Advanced analytical capability, comfortable with data, experimentation, and incrementality measurement.
• Experience working with or alongside customer analytics, product, and MarTech teams to drive holistic growth.
• Confidence leading agencies and internal teams, with a collaborative, low-ego leadership style.
• Curiosity about AI and how it can enhance marketing effectiveness and decision-making.

What They Offer

• Base salary in the range of £150,000 – £200,000, depending on experience.
• Meaningful equity, plus a comprehensive benefits package.
• Senior visibility and influence across the executive and product leadership teams.
• The chance to shape the growth model of a high-potential consumer fintech at a pivotal stage.
• A culture that values data, experimentation, and continuous learning.

How To Apply
If you are a commercially minded Director of Performance Marketing who wants to build and own a high-impact growth engine in London, please apply with your CV to find out more.

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Marketing Data Analyst – 12 month FTC

London – Hybrid (3 days office)
Up to £80,000 + benefits

We’re working with a FTSE 250 fintech operating a large-scale digital trading and investment platform. The business is fast-moving, data-driven, and heavily invested in analytics across marketing, product, and customer growth.

The Role

You’ll join a specialist analytics team focused on Performance Marketing, delivering insight to optimise acquisition, conversion, and campaign effectiveness.

Key areas:

• Performance marketing & campaign analysis
• A/B testing & experimentation
• Digital funnel & customer acquisition analysis
• Google Analytics reporting
• Stakeholder-facing insight & recommendations

What We’re Looking For

• Strong SQL (essential)
• Performance marketing / digital analytics experience
• A/B testing & experimentation exposure
• Google Analytics experience
• DBT exposure (nice to have)
• Tech, fintech or scale-up background preferred
• Strong communication & stakeholder skills

Why Join?

• FTSE 250 fintech environment
• Large-scale digital & customer datasets
• Strong investment in analytics
• High commercial impact & visibility

Interview Process

• Stage 1: Online SQL assessment (1 hour, Codility)
• Stage 2: Final interview (1 hour)

Find out more and apply via the link below!

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Marketing Data Analyst

London – Hybrid (3 days office)
Up to £80,000 + benefits

We’re working with a FTSE 250 fintech operating a large-scale digital trading and investment platform. The business is fast-moving, data-driven, and heavily invested in analytics across marketing, product, and customer growth.

The Role

You’ll join a specialist analytics team focused on Performance Marketing, delivering insight to optimise acquisition, conversion, and campaign effectiveness.

Key areas:

• Performance marketing & campaign analysis
• A/B testing & experimentation
• Digital funnel & customer acquisition analysis
• Google Analytics reporting
• Stakeholder-facing insight & recommendations

What We’re Looking For

• Strong SQL (essential)
• Performance marketing / digital analytics experience
• A/B testing & experimentation exposure
• Google Analytics experience
• DBT exposure (nice to have)
• Tech, fintech or scale-up background preferred
• Strong communication & stakeholder skills

Why Join?

• FTSE 250 fintech environment
• Large-scale digital & customer datasets
• Strong investment in analytics
• High commercial impact & visibility

Interview Process

• Stage 1: Online SQL assessment (1 hour, Codility)
• Stage 2: Final interview (1 hour)

Find out more and apply via the link below!

To Apply for this Job Click Here

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Head of AI & Machine Learning
$250,000 – $325,000 Base + Equity

Remote, United States. Competitive salary plus equity and benefits.

This is a rare opportunity to define and lead an AI strategy within a high-growth technology environment. You will combine hands-on machine learning expertise with strategic leadership, shaping how advanced AI capabilities drive real-world impact across a sophisticated product suite.

The Company
They are a fast-growing technology business operating within a highly data-driven environment, focused on transforming complex workflows through intelligent automation. Their platform supports large-scale data processing and decision-making for enterprise clients, helping to modernise manual, document-heavy processes. With strong backing and ambitious growth plans, they are investing heavily in AI to enhance product capability and maintain a competitive edge. This role sits at the centre of that transformation.

The Role

• Define and deliver the AI and machine learning strategy, aligning with product and business objectives
• Design, build, and deploy advanced NLP and document intelligence models for extracting and processing unstructured data
• Lead the full ML lifecycle including data ingestion, feature engineering, model development, evaluation, and deployment
• Explore and implement modern AI approaches such as large language models, embeddings, and retrieval augmented systems
• Build, mentor, and scale a high-performing machine learning team
• Collaborate with product and engineering teams to identify high-impact use cases and deliver scalable solutions
• Establish best practices for model monitoring, observability, and performance optimisation
• Provide technical and strategic guidance to senior stakeholders on AI opportunities and risks

Your Skills & Experience

• Strong commercial experience building and deploying machine learning models, particularly within NLP or document intelligence
• Expertise in processing unstructured or semi-structured data into structured outputs
• Proficiency in Python and modern machine learning frameworks such as PyTorch or similar
• Experience deploying models in production environments using cloud platforms and containerised workflows
• Proven ability to lead and develop technical teams while remaining hands-on
• Strong understanding of the full machine learning lifecycle and best practices in model evaluation and monitoring
• Ability to communicate complex technical concepts to a range of stakeholders

What They Offer

• Competitive salary and equity package
• Fully remote working with flexible arrangements
• Comprehensive healthcare and retirement benefits
• Generous holiday allowance and parental leave
• Clear progression path with the opportunity to shape and lead an AI function
• High impact role within a growing, innovation-focused business

How to Apply
If you are interested in leading cutting-edge AI initiatives in a high-growth environment, apply now to learn more.

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Senior Data Engineer

Location: Chicago, IL (Hybrid)
Pay: $125K – $145k base + bonus

Overview:
A rapidly growing financial services organisation is seeking a Senior Data Engineer to join a lean, highly collaborative data team. The company focuses on delivering transparent, customer-centric financial products and is expanding its data capabilities to support continued growth. This is a hands-on role with high visibility, where engineers work closely with business and product stakeholders and directly influence decision-making.

Responsibilities:

• Design, build, and maintain scalable data pipelines and infrastructure using modern cloud-based tools
• Develop and optimise advanced SQL transformations and Python workflows for analytics and operational use cases
• Build and enhance data warehouse layers, including data marts and legacy system consolidation
• Partner with analytics and business teams to translate requirements into well-structured datasets
• Lead initiatives such as pipeline migrations and new data product development
• Ensure data quality through testing frameworks, monitoring, and observability tooling
• Apply best practices for reliability and performance across data systems
• Operate in a fast-paced agile environment with high ownership across multiple workstreams

Must-Have Qualifications:

• 5+ years of hands-on data engineering experience
• Advanced SQL expertise (complex joins, CTEs, window functions) and strong Python skills
• Proven production experience with AWS cloud services
• Strong experience with Snowflake and modern ELT/data modelling practices
• Excellent communication skills with the ability to engage both technical and non-technical stakeholders
• Demonstrated ownership, stability, and ability to work in a fast-paced, business-facing environment

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Associate Kubernetes Engineer (AI / Machine Learning Infrastructure)

A globally recognized enterprise technology organization is hiring an Associate-level Kubernetes Engineer to join a highly strategic Machine Learning Platform Engineering team responsible for building and scaling the cloud-native infrastructure powering AI and machine learning systems across the company.

This team sits at the intersection of Kubernetes, cloud infrastructure, GPU-accelerated computing, distributed systems, and machine learning platform engineering, supporting internal data science and engineering teams building next-generation AI systems at enterprise scale.

Why This Opportunity Stands Out

The organization is making a significant long-term investment in modernizing its firm-wide AI and machine learning infrastructure, transitioning from legacy hybrid environments into fully cloud-native, Kubernetes-based platforms optimized for GPU-enabled AI workloads and large-scale model deployment.

This is an opportunity to work on infrastructure supporting the entire machine learning lifecycle – from model training and experimentation through inference and production deployment – while learning directly from a highly senior engineering team operating at exceptional scale.

Key Responsibilities

• Deploy and operate production-grade Kubernetes clusters supporting machine learning workloads
• Support internal ML engineers by maintaining infrastructure for model training, experimentation, deployment, and real-time inference
• Build and maintain GPU-enabled infrastructure environments supporting AI workloads
• Deploy and integrate machine learning tooling including Kubeflow, notebook environments, inference services, and model runtime infrastructure
• Work with cloud-native infrastructure as the organization migrates fully toward Google Kubernetes Engine (GKE)
• Support deployment and operationalization of Large Language Models (LLMs) for internal enterprise use cases
• Improve platform reliability, scalability, observability, and system performance across distributed environments

Required Experience

• Strong hands-on experience with Kubernetes (deploying workloads, not simply cluster administration)
• Experience supporting machine learning infrastructure or ML tooling on Kubernetes
• Understanding of the machine learning development lifecycle (training, experimentation, deployment, inference)
• Programming experience with Python or Go
• Experience working with cloud-native infrastructure environments
• Strong understanding of distributed systems and infrastructure reliability

Preferred Experience

• GPU workload deployment
• NVIDIA operator experience
• Kubeflow or notebook environments
• Kubernetes controllers / CRDs
• Google Kubernetes Engine (GKE)
• Exposure to production AI or LLM deployment infrastructure

Compensation & Location

• Compensation highly competitive with strong bonus structure
• Locations: New York / New Jersey, Toronto, or Dallas
• Primarily onsite environment with some team-level flexibility
• Visa sponsorship available

This is an exceptional opportunity for engineers looking to deepen expertise at the intersection of Kubernetes, AI infrastructure, cloud-native systems, and next-generation machine learning platforms operating at enterprise scale.

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VP Credit Risk – Data Science, Analytics & Strategy

Remote within US

No visa sponsorship

Up to $250,000 + Bonus

A fast‑growing SMB finance business is hiring a senior credit leader to help take an already‑strong credit operating system into its next phase.

The foundations are in place:

solid underwriting, established portfolio monitoring, deployed controls, and proven growth. The focus now is speed, automation, and intelligence – scaling ML‑driven decisioning so portfolio insights translate directly into automated offers, pricing, and limit actions across the credit funnel.

This role is designed to add deep external ML and analytics firepower to the organisation – not just to refine rules, but to help push credit strategy into the future and spearhead credit analytics for the organisation.

What you’ll be responsible for

• Owning credit policy and analytics across origination, portfolio monitoring, and customer management.
• Leading the next generation of ML‑driven credit models, including portfolio‑level modelling, monitoring, drift detection, and retraining strategy.
• Helping transition credit decisions toward increasingly automated offers and funnels, without sacrificing risk discipline.
• Translating portfolio signals into clear policy, pricing, and growth actions at speed.
• Partnering closely with Product, Engineering, and Operations to productionise analytics into decision engines.
• Acting as a visible senior leader and external benchmark for the credit and analytics team to aspire to.

What they’re looking for

• 8-12+ years in credit, decision science, analytics, or risk within fintech, SMB lending, cards, or adjacent data‑intensive environments.
• Very strong ML and analytics fundamentals, especially applied to portfolio‑level decisioning.
• Experience working in businesses where data and models directly drive live credit decisions.
• Comfortable moving beyond rule‑based credit toward more automated, model‑driven strategies.
• SMB experience preferred, but equally valuable is proven work in messy, real‑world credit environments.
• A leader who can both raise the technical bar and inspire the next layer of talent.

Why this role is interesting

• Credit and analytics fundamentals are already strong – this is about propelling the system forward, not rebuilding it.
• Significant scope to shape how ML is embedded into credit strategy over the next few years.
• High visibility role with real influence over product direction and growth.
• Opportunity to be the external reference point in a scaling credit organisation.

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Staff Data Scientist – Credit Risk & Marketplace

Up to $280k base + significant equity

New York | In‑office (3-4 days/week)

We’re partnering with a Series A fintech building a credit‑led marketplace – a platform where data science sits at the heart of both credit decisioning and marketplace optimisation.

This is a rare opportunity to join at a stage where models are still being defined, not inherited. The team is hiring a Senior to Staff‑level Data Scientist to help shape the decision engine that determines who gets access to credit, how risk is priced, and how the marketplace allocates supply and demand.

They’re open to two backgrounds – but only at the very top end of the market:

• Credit / lending data scientists
• Elite marketplace data scientists (pricing, ranking, matching, experimentation)
• ✅ Successful Series A (o similar) experience is strongly preferred

Why This Role Is Different

Most DS roles optimise metrics. This one moves money. Your models will directly impact:

• Credit approval decisions
• Pricing and margin
• Portfolio performance and growth velocity

This is not a reporting or support role – it’s a core decision‑making seat for someone with a high grade ML / Data Science skillset.

What You’ll Do

• Design, build and iterate on credit underwriting and pricing models used in live production
• Tackle high‑stakes, constrained optimisation problems across credit and marketplace decisioning
• Apply causal and experimental thinking where clean A/B tests aren’t possible
• Own the full lifecycle: EDA → modelling → deployment, partnering closely with engineering
• Help define modelling standards, trade‑offs, and decision frameworks at an early stage

Who They’re Looking For

• Staff‑level Data Scientist
• Strong preference for successful Series A (or early Series B) experience
• Background in credit, lending, fintech, BNPL, or adjacent decisioning‑heavy domains like marketplace
• PhD or PhD‑level rigour strongly preferred (but not required if experience demonstrates depth)
• Strong Python & SQL; comfortable owning production‑facing logic
• Someone who thrives in ambiguity, speed, and ownership

Compensation & Logistics

• Base salary up to $280k (depending on level)
• Significant equity
• NYC based, 3-4 days in office
• No visa sponsorship
• If you’ve already helped scale a Series A company – and want to do it again with real ownership and influence – this is a rare opportunity.

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Overview

We are hiring a Senior ML Engineer / Applied Scientist to build and improve production machine learning systems that power real-time fraud and risk decisions at global scale.

This is a hands-on role focused on solving complex machine learning problems from first principles. You’ll work on models that influence millions of customer transactions, own experimentation end-to-end, and help shape the future of a rapidly growing fintech platform.

This is not a role for someone simply deploying pre-built models or integrating AI APIs. We are looking for candidates who can take an ambiguous business problem, design a solution, validate it scientifically, and deliver measurable impact in production.

What You’ll Do

Build and Improve Fraud Detection Models

• Design, develop, and deploy machine learning models used for real-time fraud detection
• Develop ensemble modeling approaches that improve decision quality and model performance
• Create new predictive features and signals from large-scale transaction data
• Improve fraud detection accuracy while maintaining a strong customer experience

Drive Experimentation and Model Innovation

• Design and execute machine learning experiments from hypothesis through deployment
• Build robust offline evaluation methodologies and validation frameworks
• Develop new approaches for measuring model effectiveness prior to production release
• Apply statistical methods to evaluate model improvements and business impact

Own ML Systems End-to-End

• Build and maintain scalable machine learning pipelines
• Work with distributed data processing systems using Spark
• Partner with Product, Engineering, and Risk teams to translate business challenges into technical solutions
• Own projects through the full ML life-cycle, from concept to production

What We’re Looking For

Required Experience

• 4+ years of experience developing machine learning solutions in production environments
• Strong proficiency in Python, SQL, and Spark
• Deep understanding of machine learning, statistics, and experimental design
• Experience building models from scratch rather than primarily consuming third-party AI services
• Strong knowledge of model evaluation methodologies and performance measurement
• Experience working with large-scale datasets in distributed environments
• Ability to own technical initiatives from ideation through deployment

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Senior Product Manager
Greater Chicago Area (Hybrid)
$120,000 – $150,000 + Bonus

The Opportunity

We’re partnering with a high-growth financial technology company looking to hire two Senior Product Managers to own critical product initiatives.

This is a genuine ownership role where you’ll define strategy, solve complex business problems, and work closely with Engineering, Operations, and senior leadership to deliver products that drive measurable business impact. The environment suits someone who enjoys building from first principles, thrives in ambiguity, and wants significant autonomy.

Responsibilities

• Own the strategy, roadmap, and success of a core product area
• Identify opportunities to improve customer experience and operational efficiency
• Partner with engineering to deliver high-impact product enhancements
• Use data and SQL to guide product decisions and prioritization
• Lead product discovery, experimentation, and optimization initiatives
• Balance customer needs, business goals, and technical constraints

What We’re Looking For

• 5+ years of Product Management experience
• Proven experience owning products from concept through delivery
• Strong analytical mindset with hands-on SQL experience
• Comfortable working closely with engineering teams
• Experience solving ambiguous business problems with limited direction
• Background in high-growth, product-led organizations is highly preferred

Why Join?

• Own products with direct business impact
• Work in a lean, empowered Product organization
• High visibility with executive leadership
• Significant autonomy and opportunity to influence product strategy
• Competitive compensation and bonus

If you’re interested in learning more, apply directly or reach out for a confidential conversation.

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Head of Engineering – eCommerce

Location: Mountain View, CA (3 days/week on site minimum)

Compensation: $300,000-$325,000 base + bonus + RSUs

About the Company

Harnham is partnering with a Fortune 500 leader in cybersecurity and digital trust, combining the scale of a global enterprise with the agility of a startup culture. The company protects hundreds of millions of users worldwide, boasts best-in-class retention, and maintains an unwavering commitment to innovation.

Its platform processes over half a million telemetry events per second, and following a major fintech acquisition in 2025, the organization has significantly expanded its footprint in New York City.

The Role

They are looking for a Head of eCommerce Engineering to oversee a growing global engineering team of 20+ professionals. This is a highly visible, reporting directly to the executive team and partnering with the C-suite.

Key responsibilities include:

• Lead architecture and technical direction for global eCommerce platforms, modernizing legacy Java systems into AI-enabled solutions
• Oversee checkout, billing, subscriptions, payments, and third-party payment integrations at global scale
• Drive cloud and database modernization strategies, including Azure/AWS and OracleDB migration planning
• Provide hands-on architectural guidance, influence AI adoption, and elevate engineering capabilities across teams
• Partner with senior engineers, architects, and cross-functional leaders to improve scalability, reliability, and engineering practices while challenging legacy approaches

Ideal Candidate Profile

• 12+ years of experience preferred, with expertise in large-scale eCommerce, payments, platform modernization, and AI-assisted system design
• Background in high-scale consumer platforms and leading legacy-to-modern transformation initiatives
• BS in Computer Science or related field required; MS preferred
• Strong Java backend, system architecture, and cloud experience (Azure required, AWS a plus)
• Experience with commerce platforms, React, code/architecture reviews, and leading global engineering teams
• Proven ability to influence technical direction and challenge legacy approaches with credibility
• Preferred experience in payments, subscription billing, AI-driven modernization, OracleDB migrations, and cybersecurity/fintech domains

BENEFITS

The compensation package contains a base salary, bonus, RSUs and a comprehensive benefits package.

HOW TO APPLY

Please register your interest by sending your CV via the Apply link on this page.

KEY TERMS

Software Engineering | Leadership | eCommerce | Engineering | Fintech | Customer | Customer-Facing | Direct-to-Consumer | B2C | Product | Production | Real Time | Director | Regulation | Payments | Compliance | Regulatory | Startup Environment | Executive | Scale | Scaling | Artificial Intelligence | Java | Billing | Real-Time

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