Forward Deployed AI Engineer (Contract)
London / £500 - £600 day
INFO
RATE:
£500 - £600
LOCATION
London
Contract
Forward Deployed AI Engineer
London, 2 Days On Site
Part time - 3 days Per Week
12 Months Long
Outside IR35
£450 - £550 Per Day
The Company
They are a specialist investment-focused organisation with a portfolio of businesses across multiple sectors. They are actively exploring how AI can enhance operations, improve workflows, and unlock efficiencies across their portfolio. With a collaborative and entrepreneurial culture, they are looking for an experienced contractor who can influence strategy while remaining hands-on with delivery.
The Role and Deliverables
- Assess existing business processes and identify opportunities for AI-driven automation and optimisation.
- Design and build AI solutions using technologies such as LLMs, agents and retrieval-augmented generation (RAG).
- Create practical roadmaps for AI adoption, including prioritised implementation plans.
- Engage with business stakeholders to communicate opportunities, risks and recommendations.
- Develop, deploy and scale production-ready AI applications.
- Support portfolio businesses with AI strategy and solution implementation where required.
Your Skills & Experience
- Strong experience designing and delivering end-to-end AI solutions in commercial environments.
- Capability to work across strategy, architecture and hands-on engineering.
- Expertise with LLMs, AI agents, RAG frameworks and modern AI tooling.
- Experience assessing business processes and translating requirements into technical solutions.
- Strong stakeholder management and communication skills.
- Background working within smaller, high-growth businesses, consultancies or project-based environments.
How to Apply
If you are interested in a contract opportunity where you can shape AI strategy and build impactful solutions, please apply with your latest CV.
CONTACT
Lotte Freeman
Recruitment Executive
SIMILAR
JOB RESULTS
Data Analyst II
USA
$80000 - $100000
+ Advanced Analytics & Marketing Insights
PermanentUSA
To Apply for this Job Click Here
Data Analyst II – Product Experimentation & Analytics
United States: Fully Remote
Compensation: USD $80,000-$100,000 base + 10% target bonus
Canada: Montreal, QC
Compensation: CAD $75,000-$95,000 base + 10% target bonus
Equity: None
Work Authorization (U.S.): U.S. Citizens and Green Card holders
About the Company
This growing consumer technology organization builds digital products designed to help people better understand and improve their health and wellbeing. The business is entering an important stage of growth, expanding its offering while investing more heavily in experimentation, analytics, and data-informed product development.
You’ll join a small, collaborative environment where Data works directly with Product and Engineering. Analysts are expected to go beyond reporting-asking the right questions, challenging assumptions, and using experimentation and user behavior data to influence what gets built next.
About the Role
The Data Analyst II will become a key analytics partner to the Product organization, with approximately 70% of the role focused on experimentation and 30% on broader product analytics.
This isn’t a role focused on building dashboards and responding to ad hoc requests.
You’ll partner directly with Product Managers to design experiments, determine how success should be measured, analyze results, and translate findings into recommendations that influence product decisions.
The initial priority is improving the quality and reliability of the existing experimentation program. From there, you’ll help scale the volume of testing while establishing stronger experimentation processes and measurement standards.
You’ll also take ownership of the team’s product analytics platform, partnering with Product and Engineering on event tracking, instrumentation, dashboards, and self-service analytics.
Key Responsibilities
- Partner directly with Product Managers throughout the experimentation lifecycle
- Design, measure, and analyze A/B tests and translate results into clear product recommendations
- Improve experimentation methodology, measurement quality, and decision-making
- Help scale a growing experimentation program while maintaining testing quality
- Own product analytics across Mixpanel or a comparable platform
- Define metrics and event-tracking requirements alongside Product and Engineering
- Establish new product events, requirements documentation, validation, and QA
- Build and maintain dashboards that enable Product teams to answer questions independently
- Analyze user behavior, conversion, engagement, and product performance
- Review historical experiments and identify opportunities to improve future testing
- Translate complex analysis into clear insights for technical and non-technical stakeholders
Must Haves
- 2-4 years of Product Analytics, Data Analytics, or similar experience
- Strong hands-on A/B testing and experimentation experience
- Experience owning experiments from initial design through analysis and recommendations
- Experience with Mixpanel, Amplitude, or a comparable product analytics platform
- Strong working knowledge of SQL
- Experience partnering directly with Product Managers
- Understanding of product instrumentation, event tracking, and metric definition
- Direct-to-consumer product experience
- Strong communication and stakeholder management skills
- Ability to turn analysis into clear product recommendations rather than simply presenting results
Nice to Have
- Mobile application analytics experience
- Experience working in a high-experimentation product environment
- Consumer health or digital health experience
- Experience improving or scaling an existing experimentation program
- Experience creating self-service product analytics environments
Why Join
- Become a core analytics partner to Product rather than operating as a reporting resource
- Own experimentation from initial hypothesis through product recommendation
- Help improve and scale an experimentation program at an important stage of growth
- Work directly with Product and Engineering on how user behavior is measured
- Have meaningful influence over product decisions within a small, highly collaborative team
- Work on a consumer-facing digital product where experimentation directly impacts the user experience

To Apply for this Job Click Here
Private Cloud Architect
Dallas
$200000 - $210000
+ Data Engineering
PermanentDallas, Texas
To Apply for this Job Click Here
Private Cloud Architect
Location: Dallas, TX
Work Model: Onsite – 5 days per week
Compensation: $200,000-$210,000 base + bonus + equity
About the Company
This established enterprise organization is making a significant investment in modernizing its infrastructure and building a next-generation private cloud platform.
The goal is to bring public-cloud-style capabilities into the data center-giving engineering teams secure, automated, self-service access to compute, storage, networking, and platform services while creating a consistent experience across private and public cloud environments.
The engineering culture values technical ownership, automation, strong architectural judgment, and leaders who remain close to the technology while defining long-term platform direction.
About the Role
This is a senior, hands-on architecture role responsible for defining and evolving an enterprise private cloud platform.
You’ll lead the transition from traditional data center infrastructure toward a modern, software-defined platform built around Kubernetes, Infrastructure as Code, automation, APIs, and self-service capabilities.
A major part of the mandate is creating an internal cloud experience that gives developers the speed and usability they expect from public cloud while maintaining the control, performance, security, and reliability required within an enterprise data center.
You’ll also shape how private infrastructure integrates with AWS, Azure, and GCP to create a cohesive hybrid cloud architecture.
Key Responsibilities
- Define the architecture and long-term strategy for enterprise private cloud infrastructure
- Design cloud-native platforms across compute, storage, networking, and shared platform services
- Build and evolve Kubernetes-based environments using OpenShift, Rancher, or comparable technologies
- Develop self-service infrastructure capabilities through APIs, automation, and developer-friendly interfaces
- Design hybrid architectures connecting private infrastructure with public cloud environments
- Establish Infrastructure as Code and automation standards using Terraform or similar technologies
- Architect highly available and resilient distributed infrastructure at enterprise scale
- Modernize legacy infrastructure and transition workloads toward cloud-native architectures
- Design infrastructure capable of supporting high-performance computing and GPU-intensive workloads
- Partner with networking, security, SRE, and application engineering teams on end-to-end platform architecture
- Establish platform governance, security, observability, and operational standards
- Provide architectural leadership while remaining technically close to implementation
Must Haves
- 8+ years of infrastructure, cloud, platform engineering, or architecture experience
- Deep experience designing private cloud or large-scale data center infrastructure
- Strong Kubernetes experience, ideally including OpenShift or Rancher
- Experience designing hybrid architectures spanning on-premises infrastructure and AWS, Azure, or GCP
- Strong Infrastructure as Code and automation experience, including Terraform
- Experience designing highly available, scalable distributed systems
- Strong understanding of compute, storage, networking, and platform infrastructure
- Experience with CI/CD, GitOps, and infrastructure automation
- Ability to define architecture while remaining technically hands-on
- Experience modernizing established enterprise infrastructure rather than exclusively working in public cloud
Nice to Have
- Internal developer platforms, private cloud portals, or self-service infrastructure
- Advanced data center networking, including L2/L3 architecture and segmentation
- EVPN/VXLAN or software-defined networking
- Kafka, Spark, Flink, or similar distributed data technologies
- GPU or HPC infrastructure
- Grafana, Prometheus, and modern observability platforms
- IAM, identity integration, or Zero Trust architecture
- Microservices architecture
- Experience operating across multiple public cloud providers
Why Join
- Architect a private cloud platform rather than simply maintain traditional infrastructure
- Build an internal cloud experience that brings automation and self-service capabilities into the enterprise data center
- Own major architectural decisions across Kubernetes, compute, storage, networking, automation, and hybrid cloud
- Lead the modernization of legacy infrastructure into scalable cloud-native platforms
- Remain technically hands-on while having significant influence over long-term platform strategy
- Work on complex infrastructure challenges including hybrid cloud, distributed systems, GPU/HPC workloads, and advanced networking

To Apply for this Job Click Here
Public Cloud Architect
Dallas
$200000 - $210000
+ Data Engineering
PermanentDallas, Texas
To Apply for this Job Click Here
ublic Cloud Architect
Location: Dallas, TX
Work Model: Onsite – 5 days per week
Compensation: $200,000-$215,000 base + bonus + equity
About the Company
This established enterprise organization is making a significant investment in the modernization of its cloud infrastructure and platform engineering capabilities.
The technology organization is building a secure, automated, and scalable cloud foundation that enables engineering teams to consume infrastructure through standardized, self-service patterns. The environment is AWS-first while supporting Azure and GCP where appropriate, creating an opportunity to influence cloud strategy across a large and complex technology ecosystem.
The culture emphasizes technical ownership, strong engineering standards, automation, security, and giving architects the ability to remain hands-on while setting long-term technical direction.
About the Role
This is a senior, hands-on architecture role with ownership over the evolution of the enterprise public cloud platform.
You’ll define how cloud infrastructure is designed, governed, automated, secured, and consumed across the organization, with AWS as the primary platform. You’ll own architecture across multi-account environments, landing zones, networking, security, Infrastructure as Code, Kubernetes, cost governance, and developer enablement.
This isn’t an architecture role where you’ll simply produce diagrams. You’ll remain close to the technology, build reusable infrastructure patterns, establish engineering standards, and enable application teams to consume cloud services securely and at scale.
Key Responsibilities
- Own the architecture and evolution of a large-scale, multi-account AWS environment
- Design AWS Organizations structures, account provisioning, landing zones, and governance controls
- Build automated cloud foundations using Terraform and Infrastructure as Code
- Architect enterprise cloud networking across VPCs, private connectivity, segmentation, and hybrid environments
- Define cloud security standards across identity, access, threat detection, configuration, and network security
- Develop reusable infrastructure modules and automation patterns for engineering teams
- Establish scalable cloud governance, naming, tagging, and compliance standards
- Drive cloud cost optimization and infrastructure efficiency
- Enable engineering teams through self-service infrastructure, reusable patterns, documentation, and architecture guidance
- Support Kubernetes-based workloads across managed cloud environments
- Extend cloud governance and architectural patterns across Azure and GCP where required
- Partner with engineering, security, infrastructure, and business teams on major cloud architecture decisions
Must Haves
- 8+ years of cloud architecture, platform engineering, or infrastructure experience
- Deep, hands-on AWS architecture expertise
- Strong experience designing and governing multi-account AWS environments
- Experience with AWS Organizations, Control Tower, landing zones, and automated account provisioning
- Advanced Terraform experience for infrastructure automation at enterprise scale
- Strong AWS networking knowledge across VPCs, Transit Gateway, Direct Connect, and private connectivity
- Experience implementing enterprise cloud security and IAM controls
- Experience with managed Kubernetes platforms such as EKS
- Strong understanding of CI/CD and GitOps infrastructure delivery
- Ability to define architecture while remaining technically hands-on
- Experience operating within large, complex enterprise environments
Nice to Have
- Azure or GCP cloud architecture experience
- CloudFormation
- FinOps and cloud cost optimization
- Cloud security and compliance frameworks
- Advanced network security architecture
- Cloud observability and monitoring
- Identity federation and Zero Trust architecture
- OpenShift
- GPU or high-performance computing infrastructure
- Internal developer platforms and self-service cloud tooling
- AWS Professional-level or equivalent cloud certifications
Why Join
- Own the architecture of an enterprise-scale public cloud platform
- Define the organization’s future-state AWS strategy rather than simply maintaining an existing environment
- Build the automation, governance, and self-service capabilities used by engineering teams across the business
- Remain technically hands-on while having significant architectural influence
- Work across AWS, Terraform, Kubernetes, cloud networking, security, automation, and multi-cloud architecture
- Solve complex challenges around scale, security, developer experience, and cloud economics
- High-visibility opportunity with significant ownership over long-term cloud strategy

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Forward Deployed AI Engineer (Contract)
London
£500 - £600
+ Data Science & AI
ContractLondon
To Apply for this Job Click Here
Forward Deployed AI Engineer
London, 2 Days On Site
Part time – 3 days Per Week
12 Months Long
Outside IR35
£450 – £550 Per Day
The Company
They are a specialist investment-focused organisation with a portfolio of businesses across multiple sectors. They are actively exploring how AI can enhance operations, improve workflows, and unlock efficiencies across their portfolio. With a collaborative and entrepreneurial culture, they are looking for an experienced contractor who can influence strategy while remaining hands-on with delivery.
The Role and Deliverables
- Assess existing business processes and identify opportunities for AI-driven automation and optimisation.
- Design and build AI solutions using technologies such as LLMs, agents and retrieval-augmented generation (RAG).
- Create practical roadmaps for AI adoption, including prioritised implementation plans.
- Engage with business stakeholders to communicate opportunities, risks and recommendations.
- Develop, deploy and scale production-ready AI applications.
- Support portfolio businesses with AI strategy and solution implementation where required.
Your Skills & Experience
- Strong experience designing and delivering end-to-end AI solutions in commercial environments.
- Capability to work across strategy, architecture and hands-on engineering.
- Expertise with LLMs, AI agents, RAG frameworks and modern AI tooling.
- Experience assessing business processes and translating requirements into technical solutions.
- Strong stakeholder management and communication skills.
- Background working within smaller, high-growth businesses, consultancies or project-based environments.
How to Apply
If you are interested in a contract opportunity where you can shape AI strategy and build impactful solutions, please apply with your latest CV.

To Apply for this Job Click Here
Lead Data Scientist
Atlanta
$140000 - $150000
+ Data Science & AI
PermanentAtlanta, Georgia
To Apply for this Job Click Here
Lead Data Scientist
$140,000-$150,000 + 10% bonus
Overview
A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.
Key Responsibilities
Project Leadership & Stakeholder Management
- Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
- Independently lead projects from problem definition through deployment and performance monitoring.
- Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
- Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
- Present findings and recommendations to leadership teams, including executive audiences.
Advanced Analytics & Data Science
- Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
- Design segmentation frameworks using clustering and classification techniques.
- Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
- Identify patterns, root causes, and opportunities through large-scale data analysis.
- Develop innovative analytical approaches to improve insight generation and operational effectiveness.
- Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.
Data Management & Process Improvement
- Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
- Establish data quality standards and controls to improve accuracy and consistency.
- Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
- Monitor and assess the ongoing performance of implemented analytical solutions.
Executive Communication
- Translate complex analytical findings into actionable business recommendations.
- Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.
Required Qualifications
- Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
- 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
- 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
- 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
- Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
- Demonstrated experience analysing large structured and unstructured datasets.
- Experience presenting analytical insights to executive audiences and influencing strategic decisions.
- Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
- Strong project management, prioritisation, and multitasking skills.
- Proven ability to work independently in a fast-paced, evolving environment.
- Experience sourcing, validating, and integrating data from multiple systems and platforms.
Preferred Qualifications
- Master’s degree in a quantitative discipline.
- Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
- Experience using consumer, credit, demographic, or third-party external datasets.
- Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
- Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
- Familiarity with model risk management frameworks and third-party model review processes.
- Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
- Experience with modern data warehouse technologies.

To Apply for this Job Click Here
Lead Data Scientist
Dallas
$140000 - $150000
+ Data Science & AI
PermanentDallas, Texas
To Apply for this Job Click Here
Lead Data Scientist
$140,000-$150,000 + 10% bonus
Overview
A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.
Key Responsibilities
Project Leadership & Stakeholder Management
- Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
- Independently lead projects from problem definition through deployment and performance monitoring.
- Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
- Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
- Present findings and recommendations to leadership teams, including executive audiences.
Advanced Analytics & Data Science
- Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
- Design segmentation frameworks using clustering and classification techniques.
- Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
- Identify patterns, root causes, and opportunities through large-scale data analysis.
- Develop innovative analytical approaches to improve insight generation and operational effectiveness.
- Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.
Data Management & Process Improvement
- Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
- Establish data quality standards and controls to improve accuracy and consistency.
- Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
- Monitor and assess the ongoing performance of implemented analytical solutions.
Executive Communication
- Translate complex analytical findings into actionable business recommendations.
- Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.
Required Qualifications
- Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
- 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
- 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
- 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
- Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
- Demonstrated experience analysing large structured and unstructured datasets.
- Experience presenting analytical insights to executive audiences and influencing strategic decisions.
- Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
- Strong project management, prioritisation, and multitasking skills.
- Proven ability to work independently in a fast-paced, evolving environment.
- Experience sourcing, validating, and integrating data from multiple systems and platforms.
Preferred Qualifications
- Master’s degree in a quantitative discipline.
- Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
- Experience using consumer, credit, demographic, or third-party external datasets.
- Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
- Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
- Familiarity with model risk management frameworks and third-party model review processes.
- Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
- Experience with modern data warehouse technologies.

To Apply for this Job Click Here
Lead Data Scientist
Tempe
$140000 - $150000
+ Data Science & AI
PermanentTempe, Arizona
To Apply for this Job Click Here
Lead Data Scientist
$140,000-$150,000 + 10% bonus
Overview
A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.
Key Responsibilities
Project Leadership & Stakeholder Management
- Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
- Independently lead projects from problem definition through deployment and performance monitoring.
- Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
- Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
- Present findings and recommendations to leadership teams, including executive audiences.
Advanced Analytics & Data Science
- Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
- Design segmentation frameworks using clustering and classification techniques.
- Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
- Identify patterns, root causes, and opportunities through large-scale data analysis.
- Develop innovative analytical approaches to improve insight generation and operational effectiveness.
- Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.
Data Management & Process Improvement
- Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
- Establish data quality standards and controls to improve accuracy and consistency.
- Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
- Monitor and assess the ongoing performance of implemented analytical solutions.
Executive Communication
- Translate complex analytical findings into actionable business recommendations.
- Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.
Required Qualifications
- Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
- 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
- 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
- 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
- Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
- Demonstrated experience analysing large structured and unstructured datasets.
- Experience presenting analytical insights to executive audiences and influencing strategic decisions.
- Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
- Strong project management, prioritisation, and multitasking skills.
- Proven ability to work independently in a fast-paced, evolving environment.
- Experience sourcing, validating, and integrating data from multiple systems and platforms.
Preferred Qualifications
- Master’s degree in a quantitative discipline.
- Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
- Experience using consumer, credit, demographic, or third-party external datasets.
- Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
- Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
- Familiarity with model risk management frameworks and third-party model review processes.
- Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
- Experience with modern data warehouse technologies.

To Apply for this Job Click Here
Lead Data Engineer
London
£70000 - £85000
+ Data Engineering
PermanentLondon
To Apply for this Job Click Here
Lead Data Engineer
Up to £85,000
Holborn, London (4 days a week in office)
This is an opportunity to take ownership of a Data Engineering function at a high-growth AI-driven SaaS business. Working directly with senior technology leadership, you will combine hands-on engineering with team leadership, helping to shape the technical direction, standards and future growth of the function.
THE COMPANY
They are a rapidly scaling SaaS organisation that helps businesses unlock greater value from their data through advanced analytics and AI-powered products. Their technology supports enterprise clients across a range of sectors, delivering actionable insights that improve decision-making and commercial performance.
THE ROLE
As a Lead Data Engineer, you will be responsible for leading Data Engineering whilst remaining heavily involved in technical delivery.
Specifically, you can expect to be involved in the following:
- Building and developing the Data Engineering function, including processes, standards and best practices
- Leading, mentoring and managing a team of Data Engineers
- Designing and delivering scalable ETL and ELT pipelines across cloud environments
- Owning data modelling, architecture and platform design decisions
- Collaborating with Product, Data Science, Platform and Client Success teams
- Driving improvements across CI/CD, DevOps and engineering workflows
- Working with clients and stakeholders to understand data challenges and deliver value-driven solutions
SKILLS AND EXPERIENCE
The successful Lead Data Engineer will have the following skills and experience:
- Previous experience leading or managing a Data Engineering team
- Strong commercial experience with SQL and Python
- Expertise in building scalable ETL and ELT pipelines
- Strong understanding of data modelling and modern data architecture principles
- Experience working with cloud platforms such as Azure, AWS or GCP
- Knowledge of Databricks, Azure Data Factory, Microsoft Fabric or similar modern data platforms
- Experience with Git, CI/CD and DevOps best practices
- Strong communication skills with the ability to engage technical and non-technical stakeholders
- Experience in consulting, client-facing or project-led environments would be advantageous
BENEFITS
The successful Lead Data Engineer will receive the following benefits:
- Salary up to £85,000 – depending on experience
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

To Apply for this Job Click Here
Azure Cloud Engineer
Abingdon
£40000 - £50000
+ Data Engineering
PermanentAbingdon, Oxfordshire
To Apply for this Job Click Here
Azure Cloud Engineer
£40,000 – £50,000
Abingdon, Oxfordshire (1 day a week in office)
Looking to take ownership of real Azure infrastructure while broadening your exposure to cloud architecture, AI initiatives, and large-scale transformation projects? This is an opportunity to join a growing cloud team where you’ll have a direct impact on both internal platforms and client-facing technology programmes.
THE COMPANY
This consultancy-led organisation delivers technology, cloud, and transformation solutions across a diverse portfolio of public and private sector clients. They are continuing to invest heavily in cloud and AI capabilities and are growing their internal cloud function to support increasing demand. Operating within a fully cloud-native Microsoft Azure environment, the team is responsible for all cloud infrastructure, security, governance, and platform services across the business. You’ll join a collaborative technology team where innovation, practical problem-solving, and continuous improvement are highly valued.
THE ROLE
As an Azure Cloud Engineer, you will support the design, delivery, and ongoing management of cloud infrastructure while working closely with consultants and programme teams across the business.
Specifically, you can expect to be involved in the following:
- Building, supporting, and optimising Microsoft Azure environments
- Managing cloud resources including Virtual Machines, SQL Servers, Web Apps, and containerised applications
- Supporting Azure DevOps and GitHub-based development and deployment processes
- Creating and maintaining CI/CD pipelines
- Assisting with cloud architecture and infrastructure design discussions
- Advising stakeholders on cloud hosting approaches and infrastructure best practices
- Supporting cloud cost optimisation and operational efficiency across the estate
SKILLS AND EXPERIENCE
The successful Azure Cloud Engineer will have the following skills and experience:
- Commercial experience working within Microsoft Azure environments
- Experience deploying and supporting cloud infrastructure end-to-end
- Knowledge of Azure services including compute, networking, storage, and identity management
- Experience with Azure DevOps and/or GitHub
- Experience building and supporting CI/CD pipelines
- Understanding of cloud security, governance, and compliance principles
- Strong stakeholder communication skills and the ability to work with both technical and non-technical teams
BENEFITS
The successful Azure Cloud Engineer will receive the following benefits:
- Salary between £40,000 – £50,000 – depending on experience
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

To Apply for this Job Click Here
Software Engineer – Treasury
London
£180000 - £200000
+ Data Engineering
PermanentLondon
To Apply for this Job Click Here
Software Engineer – Treasury
Up to £200,000
London (4-5 days a week in office)
If you are looking for a software engineering role that combines technical ownership, business impact, and exposure to front, middle, and operational functions within a sophisticated investment environment, this opportunity offers a rare chance to build and own critical systems that support a global financial organisation. You will work closely with business stakeholders, solve complex problems, and see the direct impact of your work across the organisation.
THE COMPANY
They are a globally operating investment firm with a strong engineering culture and a significant focus on technology, automation, and innovation. Technology teams are embedded within the business and play an essential role in driving operational efficiency and supporting key investment functions.
Their Enterprise Engineering team develops and maintains business critical platforms spanning treasury, fund accounting, compliance, and middle office operations. Engineers are trusted with genuine ownership and are encouraged to contribute ideas, challenge processes, and deliver meaningful improvements.
THE ROLE
As a Software Engineer you will join a high-performing engineering team building mission-critical software that powers core operations across a leading investment firm.
Specifically, you can expect to be involved in the following:
- Design, build, and maintain production software used across treasury, fund accounting, compliance, and middle office functions
- Take ownership of systems and applications from development through to deployment and ongoing enhancement
- Collaborate closely with business stakeholders to understand requirements and deliver practical solutions
- Work across a mix of modern Python services and established object-oriented codebases
- Contribute to architectural discussions and system design decisions
- Partner with teams across technology and operations to solve complex business challenges
SKILLS AND EXPERIENCE
The successful Software Engineer will have the following skills and experience:
- Strong commercial software engineering experience with Python in a production environment
- Experience with at least one object-oriented programming language such as Java, C#, or C++
- Strong SQL skills and experience working with relational databases
- Background within buy-side financial services, hedge funds, asset management, or prime brokerage environments
- Ability to communicate technical concepts clearly to both technical and non-technical stakeholders
- Knowledge of treasury, fund accounting, middle office, financing, stock loan, or related operational functions is highly desirable
BENEFITS
The successful Software Engineer will receive the following benefits:
- Salary up to £200,000 – depending on experience
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

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Data Scientist Consultant (Contract)
London
£500 - £640
+ Data Science & AI
ContractLondon
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Data Scientist Consultant
Fully Remote (Need right to work in UK)
Inside IR35
£500 – £640 Per Day
Start Immediately
The Company
They are a well-established organisation with a strong focus on data-driven innovation within financial services and credit analytics. Their teams develop sophisticated modelling solutions, risk products, and decisioning tools powered by extensive commercial data assets. With continued investment in cloud technologies and advanced analytics, they are building the next generation of AI and machine learning capabilities. You will join a collaborative environment that values technical excellence, innovation, and commercial impact.
The Role and Deliverables
- Develop predictive models, credit risk scorecards, and advanced analytical solutions using large-scale financial and commercial datasets.
- Prepare, audit, cleanse, and analyse complex credit and business data to generate actionable insights.
- Design and optimise scalable data pipelines to support machine learning and analytics workflows.
- Partner with business stakeholders to translate commercial and risk challenges into data-driven solutions.
- Communicate analytical findings through clear visualisations and business-focused recommendations.
- Support the adoption of modern cloud technologies, machine learning techniques, and analytics best practice.
Your Skills & Experience
- Recent experience within financial services, credit risk, lending, credit bureaux, or commercial credit analytics is essential.
- Strong experience building predictive models, risk scorecards, or decisioning solutions within a regulated financial environment.
- Proven experience working with credit, lending, bureau, or commercial financial datasets.
- Strong Python and SQL skills for data science, analytics, and data engineering activities.
- Experience applying statistical and machine learning techniques to solve complex commercial or risk-related problems.
- Hands-on experience working within Google Cloud Platform environments.
- Understanding of model development lifecycles, model governance, validation, and version control best practices.
- Strong stakeholder management skills with the ability to communicate technical findings to non-technical audiences.
How to Apply
If you have recent experience in credit risk, lending, or financial services data science and are looking to deliver high-impact modelling projects in a modern cloud environment, apply today to learn more.

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Financial Crime Business Analyst
London
£450 - £500
+ Advanced Analytics & Marketing Insights
ContractLondon
To Apply for this Job Click Here
Contract Business Analyst – Financial Crime / FinTech
Location: London – Hybrid
Contract: 3 months
Sector: FinTech / Financial Services
We’re working with a fast-growing UK fintech looking for an experienced Business Analyst to support a key programme within its Financial Crime function.
The role will sit between Financial Crime, Product and Technology teams, helping to understand existing processes, gather requirements and translate complex regulatory and operational needs into clear, deliverable solutions.
The Role
You’ll be responsible for:
- Leading requirements gathering across Financial Crime and Compliance stakeholders
- Running workshops and translating business needs into clear functional and technical requirements
- Mapping as-is and to-be processes, identifying gaps and recommending improvements
- Producing user stories, acceptance criteria, process maps and supporting documentation
- Working closely with Product, Engineering, Data and Compliance teams throughout delivery
- Supporting improvements across Financial Crime systems, controls and customer journeys
- Managing stakeholders and ensuring requirements are understood from discovery through to implementation
Experience Required
We’re looking for someone with:
- Strong experience as a Business Analyst within banking, fintech or financial services
- Good knowledge of Financial Crime, ideally across areas such as AML, KYC/CDD, sanctions, PEP screening, transaction monitoring or fraud
- Experience delivering technology-led Financial Crime or regulatory change
- Strong requirements gathering, workshop facilitation and process-mapping experience
- Experience producing user stories, functional requirements and acceptance criteria
- Ability to work effectively between technical teams and Financial Crime/Compliance SMEs
- Strong stakeholder management skills within a fast-paced Agile environment

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