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Senior Data Scientist

London – 2x a week

The Role

As a Senior Data Scientist, you will:

• Develop and enhance credit risk and decisioning models using customer, credit bureau, transactional, and internal datasets.
• Analyse portfolio performance across originations, arrears, defaults, recoveries, and customer behaviour.
• Identify opportunities to improve underwriting strategies and customer decisioning.
• Produce actionable insights from large, complex, and sometimes incomplete datasets.
• Build monitoring frameworks and reporting to track model and portfolio performance.
• Support the deployment and optimisation of analytical solutions within production environments.
• Investigate data quality issues and drive improvements across reporting and decisioning processes.
• Work closely with risk, product, engineering, and commercial stakeholders to deliver data-driven solutions.
• Contribute to model governance, validation, and documentation activities.

Skills & Experience

• Strong Python experience across analytics, modelling, and data processing.
• Hands-on experience working within AWS environments, including services such as Lambda, EC2, SageMaker, RDS, and CloudWatch.
• Proven track record developing and validating predictive models, including logistic regression and machine learning techniques.
• Strong understanding of consumer credit risk, affordability assessment, and lending decisioning.
• Excellent analytical and problem-solving skills with a rigorous attention to detail.
• Experience translating complex analysis into clear recommendations for business stakeholders.
• A proactive, ownership-driven mindset and ability to thrive in a fast-paced environment.

What They Offer

• Competitive salary
• Be part of a fast-growing, data-led business.
• Work on high-impact projects with direct business visibility.
• Influence lending decisions and strategic direction.
• Collaborate with experienced professionals across risk, product, and technology.
• Enjoy significant autonomy and ownership in a highly collaborative environment.

How to Apply

Please get in touch to learn more about this role.

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Senior Valuations Manager
London
£120,000 to £150,000 plus benefits.

This is a high impact leadership role where you will shape how valuation and NPV models are designed and used across a modern consumer lending business. You will move beyond traditional approaches, embedding sophisticated valuation models directly into credit decisioning and strategy.

The Company
They are a fast growing, profitable digital financial services organisation operating across multiple consumer lending and banking products. With significant investment in analytics and technology, they place strong emphasis on data driven decision making. Valuations sit at the heart of their growth strategy.

The Role

• Set the strategic direction for valuation, NPV and IRR modelling across lending products
• Build and evolve account level valuation models used in live decisioning
• Partner with Credit Risk, Product, Finance and Impairment teams
• Lead and develop a team of credit analysts with close links to data science
• Drive innovation in valuation methodology and modelling infrastructure

Your Skills & Experience

• Strong commercial experience in valuation, NPV and IRR modelling within consumer lending
• Proven ability to build models from first principles
• Strong conceptual thinker with confidence to challenge existing approaches
• Python experience within modelling environments
• Effective people leadership and senior stakeholder management

What They Offer

• Salary of £120,000 to £150,000 plus benefits
• Hybrid working with flexibility
• High visibility role with genuine influence on credit and growth strategy
• Clear scope for career progression

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CRO Manager

£45,000 – £60,000

Macclesfield (3 days a week on-site)

This is an exciting opportunity for a CRO Manager to take ownership of conversion rate optimisation and experimentation within a growing digital business. Joining at a pivotal stage, you will have the chance to shape the CRO function, influence strategy, and deliver measurable commercial impact across multiple customer journeys and digital products.

THE COMPANY

They are a fast-growing digital organisation with an international presence and a diverse portfolio of online brands and products. Their business is focused on delivering high-quality customer acquisition through digital channels, supported by strong investment in marketing, technology, and data-driven decision-making.

As they continue to expand, they are bringing conversion rate optimisation in-house, creating a unique opportunity for someone to establish best practices, drive experimentation, and help build a high-performing optimisation function.

THE ROLE

As a CRO Manager, you will lead CRO strategy across multiple digital brands, products, and acquisition funnels, working closely with cross-functional teams to improve customer journeys and conversion performance.

Specifically, you can expect to be involved in the following:

• Owning the CRO and experimentation roadmap across multiple digital products
• Designing, executing, and analysing A/B and multivariate testing programmes
• Developing hypotheses based on user behaviour, analytics, and business objectives
• Identifying opportunities to improve conversion rates and customer experience
• Partnering with Product, Marketing, and Development teams to implement test plans
• Measuring, reporting, and communicating the commercial impact of experimentation
• Establishing CRO frameworks, processes, and best practices
• Supporting the future growth and development of the internal CRO capability

SKILLS AND EXPERIENCE

The successful CRO Manager will have the following skills and experience:

• Strong commercial experience in conversion rate optimisation and experimentation
• Proven success running A/B testing programmes and delivering measurable results
• Expertise in hypothesis development, test design, and optimisation methodologies
• Experience using experimentation platforms such as Optimizely, VWO, Convert.com, or similar
• Strong analytical skills with the ability to interpret user behaviour and performance data
• Confident communicating insights and influencing stakeholders across the business
• Experience within lead generation, ecommerce, digital marketing, or performance-driven environments is advantageous

BENEFITS

The successful CRO Manager will receive the following benefits:

• Salary between £45,000 – £60,000 – 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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Decision Science Lead
London
£70,000 to £90,000 plus benefits

This is an opportunity to step into a high impact Decision Science Lead role within a fast growing fintech environment. You will play a key role in shaping credit risk strategy through advanced analytics and machine learning, with strong exposure to senior stakeholders and clear progression opportunities.

The Company
They are a scaling fintech business operating in the consumer lending space, focused on delivering innovative, data driven solutions. With a strong market presence and growing customer base, they are competing with some of the largest players in the industry. The business combines a collaborative, agile culture with a clear ambition to continue expanding its analytics capability.

The Role

• Develop and enhance credit risk models including scorecards, behavioural, acquisition and fraud models
• Build predictive models using advanced statistical and machine learning techniques
• Deploy models into production using AWS SageMaker and collaborate with engineering teams
• Monitor model performance and ensure ongoing effectiveness across business and technical metrics
• Generate insights and present clear, actionable recommendations to stakeholders
• Explore new data sources and modelling approaches to drive innovation
• Work closely with cross functional teams to influence lending and risk decisions

Your Skills and Experience

• Strong commercial experience within consumer credit and lending environments
• Proven ability to develop credit risk models, including scorecards or predictive models
• Strong programming skills in Python and SQL with experience working in cloud environments such as AWS
• Solid grounding in statistics and machine learning
• Experience working with large, complex datasets and delivering business insights
• Strong communication skills with the ability to influence stakeholders
• Experience with model deployment is highly beneficial
• Exposure to dbt is desirable

What They Offer

• Salary between £70,000 and £90,000
• Hybrid working with two to three days in the office each week
• Competitive benefits package including bonus, pension and private medical cover
• Strong career progression opportunities within a growing data function
• A collaborative and supportive working environment with exposure to senior leadership

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Data Engineer (dbt & Snowflake Expert)

Location: Dallas, TX (Onsite 4 days/week)
Compensation: Up to $160,000 Base Salary + Bonus
Work Authorization: Must be authorized to work in the U.S. without sponsorship now or in the future.

Overview

We are seeking a highly skilled Data Engineer with deep expertise in dbt (Data Build Tool) and Snowflake to join our growing data and analytics team. This individual will play a key role in designing, building, and optimizing scalable data pipelines and cloud-based data solutions that enable business intelligence, analytics, and data-driven decision-making across the organization.

Experience within Financial Services, Banking, Capital Markets, Insurance, or FinTech environments is highly preferred but not required.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes using modern cloud-based technologies.
• Build, optimize, and manage data models in dbt, following best practices for testing, documentation, and maintainability.
• Develop and maintain enterprise data warehouse solutions within Snowflake.
• Partner with business stakeholders, analytics teams, and data consumers to understand and deliver data requirements.
• Optimize Snowflake performance, scalability, and cost efficiency.
• Implement data quality, governance, and monitoring frameworks to ensure accuracy and reliability.
• Create and maintain technical documentation for data architecture, models, and workflows.
• Collaborate with Data Analysts, BI Developers, and Data Scientists to support reporting and advanced analytics initiatives.
• Troubleshoot and resolve data issues, pipeline failures, and performance bottlenecks.
• Participate in architecture discussions and contribute to the overall data strategy.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field (or equivalent experience).
• 5+ years of experience in Data Engineering, Data Warehousing, or related roles.
• Expert-level experience with dbt and Snowflake.
• Strong SQL development and query optimization skills.
• Experience designing and building scalable ETL/ELT pipelines.
• Hands-on experience with cloud-based data platforms and modern data stack technologies.
• Strong understanding of data modeling principles, including dimensional and star schema design.
• Experience implementing data validation, testing, and monitoring frameworks.
• Excellent problem-solving, communication, and collaboration skills.

Preferred Qualifications

• Experience within Financial Services, Banking, Capital Markets, Insurance, or FinTech environments.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with orchestration tools such as Airflow, Prefect, or Dagster.
• Experience supporting BI and analytics platforms such as Tableau, Power BI, or Looker.
• Knowledge of CI/CD pipelines and DataOps best practices.
• Experience working in Agile development environments.

Key Skills

• Snowflake
• dbt (Data Build Tool)
• SQL
• Data Warehousing
• ETL/ELT Development
• Data Modeling
• Cloud Platforms (AWS, Azure, GCP)
• Data Governance & Quality
• Performance Optimization
• Business Intelligence & Analytics

Additional Information

• Location: Dallas, TX
• Schedule: Onsite 4 days per week
• Salary: Up to $160,000 base salary
• Bonus: Eligible for annual performance bonus
• Sponsorship: Not available. Candidates must be authorized to work in the United States without current or future sponsorship requirements.

Ideal Candidate: A hands-on Data Engineer with deep dbt and Snowflake expertise who thrives in a collaborative environment and enjoys building scalable, high-quality data solutions that drive business value. Financial services experience is a strong plus but not required.

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Analytics Engineering Manager

Location: Amsterdam, Netherlands (Hybrid)

Salary: €100-115k

This is an opportunity to lead the data foundation of a large-scale digital business where data sits at the heart of every product, analytics, and commercial decision. You will combine people leadership, technical ownership, and strategic influence while shaping a modern analytics engineering function operating at significant scale.

The Company

They are a well-established digital organisation with a strong data-driven culture and a substantial investment in data and analytics. Their teams rely on trusted, high-quality data to support decision-making across product, commercial, and leadership functions. The business is continuing to evolve its data platform, creating an opportunity for an experienced Analytics Engineering Manager to have a visible and lasting impact. You will work closely with senior stakeholders while helping to define the future direction of their data ecosystem.

The Role

You will be responsible for leading the analytics engineering capability and ensuring the data platform remains scalable, reliable, and trusted across the organisation.

Responsibilities include:

• Leading, coaching, and developing a team of Analytics Engineers and Data Engineers
• Owning data ingestion pipelines, transformation workflows, and data warehouse orchestration
• Designing and maintaining scalable data models that support analytics and business reporting
• Establishing and governing a semantic layer to ensure consistent metric definitions
• Driving automation across analytics engineering processes to improve efficiency and scalability
• Setting engineering best practices including CI/CD, code reviews, testing, and version control
• Improving platform performance, reliability, observability, and data quality standards
• Managing warehouse optimisation initiatives and controlling data platform costs
• Partnering with analytics, engineering, and business teams to align data capabilities with business needs
• Communicating platform strategy, priorities, risks, and investment requirements to senior stakeholders

Your Skills & Experience

• Strong leadership experience managing Analytics Engineering or Data Engineering teams
• Deep expertise in modern cloud-based data platforms and large-scale data warehousing environments
• Strong knowledge of ELT/ETL architecture, data modelling, and orchestration frameworks such as Airflow, dbt, or similar technologies
• Experience building reliable, observable, and well-governed data platforms
• Strong understanding of data quality, monitoring, testing, lineage, and data contracts
• Experience optimising data platform performance and managing cloud data costs
• Software engineering best practices including Git-based workflows, CI/CD, and automated testing
• Ability to balance technical leadership, delivery ownership, and people management
• Strong stakeholder management skills with the ability to communicate technical concepts to non-technical audiences
• Exposure to AI-assisted engineering workflows, automation, or productivity-enhancing tooling is advantageous
• Experience with streaming or near real-time data environments would be beneficial

What They Offer

• Opportunity to lead a strategically important data engineering function
• High levels of ownership and influence over platform direction and standards
• Exposure to complex, large-scale data challenges
• A collaborative and data-focused environment with strong executive sponsorship
• Clear opportunities for professional growth and leadership development

How to Apply

If you are an experienced Analytics Engineering Manager looking to shape the future of a modern data platform, apply now to learn more about this opportunity.

To Apply for this Job Click Here

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Lead Data Engineer

Up to £100,000
*Kafka or Kinesis required
London (4 days onsite)

This is a great opportunity to join a high‑growth organisation where you can take ownership of building and architecting a greenfield data platform for an AI‑driven product.

THE COMPANY:

This is an early-stage, venture-backed company building the operating system for modern property management through its AI platform.

THE ROLE:

You will take ownership of the entire data architecture, acting as the most senior individual contributor within Data Engineering. This is a hands-on leadership role focused on technical ownership rather than people management.
Key responsibilities include:

• Designing and owning the company’s data architecture from the ground up
• Building scalable batch and real-time data pipelines
• Developing data ingestion, storage, and transformation frameworks
• Supporting AI and machine learning infrastructure, including vector search systems
• Implementing data quality, monitoring, and observability practices
• Collaborating closely with AI, backend engineering, and product teams
• Optimising performance, scalability, and reliability of large datasets
• Influencing long-term technical strategy and laying foundations for the data function

YOUR SKILLS AND EXPERIENCE:

You will bring strong capability in:

• Python development and building scalable distributed data systems
• Data architecture design and pipeline development
• Batch and streaming data processing
• Relational databases (PostgreSQL or similar)
• NoSQL and modern vector databases (e.g., Qdrant, Milvus, pgvector)

THE BENEFITS:

You will receive a salary of up to £100,000 depending on experience.

HOW TO APPLY:

Please register your interest by sending your CV to Molly Bird via the apply link on this page.

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Research Engineer, Multimodal Datasets

US Remote
$400k + Equity

This is an opportunity to shape how next generation AI systems learn about the world. You will work at the intersection of data, modelling, and experimentation, owning the datasets that underpin cutting edge multimodal models. If you are motivated by high impact research and want to directly influence real world model capability, this role offers uncommon scope and ownership.

The Company
They are a well funded AI research and product organisation focused on advancing multimodal systems beyond traditional language models. Their work centres on building models that can understand and simulate complex environments across video, image, and interactive contexts. With significant recent investment and rapid growth, they operate at the frontier of generative media and real time simulation. The culture is collaborative, research driven, and focused on delivering meaningful technical breakthroughs.

The Role
You will take ownership of the data strategy behind large scale multimodal models, influencing both research direction and real world product capability.

• Design and build large scale multimodal datasets across image and video domains
• Run structured experiments to understand how dataset composition impacts model performance
• Develop and maintain pipelines for synthetic data generation, curation, and quality control
• Define robust evaluation frameworks and benchmarks aligned to real use cases
• Collaborate with research, product, and creative teams to translate goals into data strategies
• Contribute to model training workflows, including pre training and fine tuning

Your Skills and Experience

• Strong commercial experience working with large scale machine learning or foundation models
• Hands on expertise with multimodal data, particularly image or video based systems
• Deep understanding of dataset design, curation, and evaluation in model performance
• Experience working across the full ML lifecycle including training, experimentation, and analysis
• Proficiency in frameworks such as PyTorch or JAX and distributed compute tools
• Evidence of research contribution, open source work, or strong technical projects
• A curiosity driven mindset with a genuine interest in advancing AI capabilities

What They Offer

• Highly competitive compensation with equity participation
• Fully remote working with a globally distributed team
• Significant ownership and influence over core model capabilities
• Opportunity to work on frontier AI challenges with real world impact
• A fast paced, low ego environment focused on innovation and learning

How to Apply
If you are interested in shaping the future of multimodal AI systems, please apply with your CV and relevant project or publication links.

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Senior Data Scientist – START UP – EQUITY

We are working with an exciting start up company who are committed to making affordable, flexible loans for their customers. This will be their first Data Science hire in the company and will have full ownership on ML models across the business.

Required Experience:

• Experience working in Lending, Loans, Insurance or Credit businesses
• Experience building and deploying Credit Risk Data Models
• AWS, Python & SQL experience

Important Information

• 2 days a week in London
• Up to £70K base
• Equity
• No additional benefits

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Engineer (Snowflake | dbt | Fivetran)

Dallas, TX (Hybrid – 4 Days Onsite)

Salary: $140,000-$165,000 Base + Bonus (Flexible)

We’re partnering with a large, well-established enterprise that’s making a significant investment in modernizing its data platform. This is an opportunity to join a newly formed data engineering organization focused on building scalable, cloud-native solutions that will support critical business initiatives across the enterprise.

You’ll be joining early in a long-term transformation, working with modern technologies including Snowflake, dbt, Fivetran, Python, and SQL to build robust data pipelines, optimize data models, and help establish engineering best practices. Whether your expertise is centered around dbt or Fivetran, this team is looking for experienced engineers who enjoy solving complex data challenges in a collaborative environment.

What You’ll Do

• Design, build, and maintain scalable ELT pipelines using modern cloud technologies.
• Develop and optimize data models within Snowflake for analytics and reporting.
• Build and support data ingestion pipelines using Fivetran and transformation workflows using dbt.
• Develop solutions using Python and advanced SQL.
• Partner with analytics, engineering, and business teams to translate requirements into scalable data products.
• Improve data quality, testing, monitoring, and pipeline reliability.
• Contribute to CI/CD processes and Infrastructure as Code initiatives.
• Help define engineering standards and best practices across a growing enterprise data platform.

What We’re Looking For

• 5+ years of Data Engineering experience.
• Strong experience with Snowflake.
• Hands-on experience with dbt and/or Fivetran.
• Advanced SQL and Python skills.
• Experience building production-grade cloud data pipelines.
• Experience with AWS, Azure, or GCP.
• Familiarity with Git, CI/CD, and modern software development practices.

Nice to Have

• Terraform
• Kafka or streaming technologies
• Data modeling and dimensional modeling experience
• Experience with automated testing and data quality frameworks
• Financial services experience (not required)

Why Consider This Opportunity?

• Join a greenfield enterprise data transformation with strong executive sponsorship.
• Work with a modern cloud-native technology stack.
• Small, collaborative engineering team with significant growth planned.
• Opportunity to influence engineering standards and platform direction.
• Long-term career growth with continued investment in learning and development.
• Competitive compensation, bonus, and a stable organization investing heavily in its technology roadmap.

To Apply for this Job Click Here

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Position Summary

The Lead Data Solutions Engineer is responsible for designing, developing, implementing, and supporting enterprise-scale data platforms and solutions. This individual will collaborate closely with architects, engineers, analytics teams, business stakeholders, and technology partners to define best practices, establish governance standards, and drive adoption of modern data engineering methodologies.

This role serves as a subject matter expert for enterprise data solutions, providing technical leadership, mentoring team members, and guiding strategic decisions related to data architecture, engineering, and platform optimization.

Key Responsibilities

Data Platform Architecture & Engineering

• Lead the design, implementation, and governance of enterprise ETL/ELT pipelines utilizing modern cloud data technologies.
• Architect and review end-to-end data workflows from source systems through curated, analytics-ready datasets.
• Design scalable data architectures supporting ingestion, transformation, storage, and consumption layers.
• Develop reusable frameworks and patterns that improve maintainability, consistency, and efficiency across data engineering initiatives.

Snowflake & Cloud Data Solutions

• Design andoptimize Snowflake-based data platforms, including:
  • Warehouse sizing and workload management
  • Performance optimization and tuning
  • Data security and access control frameworks
  • Cost management and resource governance
• Establish best practices for enterprise-scale cloud data operations.

Analytics Engineering & Data Modeling

• Develop and govern data transformation frameworks using dbt.
• Create modular and reusable data models across staging, intermediate, and business-layer datasets.
• Implement documentation, testing, lineage tracking, and quality controls.
• Build standards that promote transparency, reliability, and self-service analytics.

Data Pipeline Development

• Design and support highly scalable data pipelines using SQL, Python, and PySpark.
• Build solutions that accommodate batch, streaming, and hybrid processing requirements.
• Oversee ingestion frameworks and ensure reliable movement of data across multiple environments and platforms.

Infrastructure Automation & DevOps

• Implement Infrastructure as Code (IaC) practices using Terraform.
• Automate provisioning and management of data platform resources.
• Design CI/CD processes supporting:
  • Automated deployments
  • Environment promotion strategies
  • Source control and release management
  • Code quality validation and testing

Data Quality & Operational Excellence

• Establish standards for monitoring, observability, and data quality management.
• Ensure data platforms are reliable, scalable, and production-ready.
• Define service-level expectations and operational support processes.
• Drive continuous improvement initiatives focused on platform stability and performance.

Technical Leadership

• Lead architecture reviews, proofs of concept, and technology evaluations.
• Mentor and coach data engineers, providing technical guidance and best practices.
• Facilitate technical discussions and represent the data engineering function in cross-functional meetings.
• Influence enterprise-wide standards, governance models, and architectural direction.

Security, Compliance & Governance

• Partner with security, platform, and compliance teams to implement enterprise data governance requirements.
• Ensure solutions meet security, regulatory, and access-control standards.
• Balance governance objectives with engineering efficiency and delivery goals.

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, Economics, or a related discipline, or equivalent practical experience.
• 7+ years of experience delivering enterprise-scale data engineering solutions.
• Demonstrated success leading large-scale data platform initiatives in cloud and/or hybrid environments.
• Strong experience building and supporting complex, high-volume data pipelines in production environments.
• Expertise in cloud data warehousing, data modeling, and modern analytics engineering practices.
• Advanced proficiency with SQL and strong hands-on experience with Python and/or PySpark.
• Experience with Snowflake, dbt, Fivetran, Terraform, and modern data ecosystem tools.
• Strong understanding of enterprise data warehousing concepts and architecture patterns.
• Experience designing, developing, testing, and deploying business intelligence and analytics solutions.
• Knowledge of CI/CD, Infrastructure as Code, and software development lifecycle best practices.
• Strong analytical, problem-solving, and systems-thinking capabilities.
• Excellent verbal and written communication skills with the ability to present complex technical concepts to both technical and non-technical audiences.
• Proven ability to lead initiatives, influence stakeholders, and drive outcomes with minimal oversight.
• Strong sense of ownership, accountability, and commitment to continuous improvement.

Preferred Experience

• Experience with AWS and/or Azure cloud environments.
• Exposure to Kafka or event-driven data architectures.
• Experience establishing data governance, metadata, and lineage frameworks.
• Background evaluating and implementing emerging data technologies.
• Experience mentoring engineering teams and contributing to enterprise architecture strategies.

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