data & AI
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Data Engineering Manager

100% Remote – United States
Salary: Up to $220,000 base + Comprehensive Benefits
U.S. Citizens or Green Card Holders Only
No Sponsorship Available Now or in the Future

A rapidly growing technology organization focused on delivering advanced data and analytics solutions is seeking a Data Engineering Manager to lead a team responsible for building scalable, cloud-based data platforms and customer data integration solutions. This is a fully remote leadership opportunity where you’ll drive technical strategy, mentor engineers, and help shape the future of a modern data ecosystem.

What You’ll Be Doing

• Lead and develop a high-performing Data Engineering team, providing mentorship, coaching, and technical direction.
• Oversee the design and delivery of scalable data platforms, ELT pipelines, and data integration frameworks.
• Drive modernization initiatives across data architecture, tooling, automation, and engineering practices.
• Partner with business and technical stakeholders to translate complex requirements into scalable solutions.
• Establish engineering standards, best practices, and quality processes to improve reliability and maintainability.
• Lead efforts around data quality, validation, observability, profiling, and monitoring capabilities.
• Evaluate emerging technologies, including AI-enabled solutions, to improve engineering productivity and automation.
• Build and execute data roadmaps that support both customer needs and long-term platform growth.

What We’re Looking For

• 12+ years of data engineering experience with increasing ownership and leadership responsibilities.
• 5+ years of experience managing or leading data engineering teams, including mentoring and developing engineers.
• Strong hands-on expertise with SQL, Python, ELT pipelines, and modern data architectures.
• Experience with orchestration and transformation tools such as Airflow, Astronomer, Dagster, dbt, or similar technologies.
• Proven background designing scalable data platforms and modernizing legacy environments.
• Experience working with complex, imperfect data from multiple sources and building standardized data models.
• Strong understanding of data quality, governance, validation, and monitoring practices.
• Excellent communication skills with the ability to influence technical and business stakeholders.
• Healthcare, public sector, SaaS, or highly regulated industry experience is highly beneficial.

Why This Opportunity?

• 100% remote within the U.S.
• Opportunity to lead critical data initiatives with significant business impact.
• High visibility role influencing technology strategy and platform direction.
• Collaborative, growth-oriented culture with strong executive support.
• Competitive compensation, bonus potential, and comprehensive benefits package.

Location: Fully Remote (U.S.)
Work Authorization: U.S. Citizen or Green Card Holder required. No sponsorship available.
Employment Type: Full-Time, Permanent

Confidential search being conducted by a recruiting partner on behalf of our client.

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Senior Agentic AI Engineer (Full Stack)
$160,000-$180,000
4 days/week on-site

Overview

We are seeking a senior software engineer with a strong full-stack background who has evolved into AI engineering and agent development. This role focuses on building, deploying, and optimising intelligent agents and AI-driven workflows that interact with enterprise systems, data sources, and users.
The successful candidate will have hands-on experience developing production-grade AI applications using large language models (LLMs), retrieval-augmented generation (RAG), agent orchestration frameworks, and modern software engineering practices. This position is centred on designing and building AI agents rather than purely traditional application development.

Key Responsibilities

AI Agent Development

• Design and develop AI agents capable of reasoning across complex business processes and interacting with tools, APIs, and enterprise systems.
• Build intelligent support and workflow automation agents that understand intent, retrieve information, and execute tasks.
• Develop agentic workflows combining LLMs, structured data, business logic, external services, and retrieval mechanisms.
• Create memory, context, and personalisation capabilities to improve agent effectiveness.
• Implement guardrails, monitoring, evaluation frameworks, escalation paths, and human oversight mechanisms.
• Measure and improve agent performance across quality, reliability, latency, utilisation, and cost metrics.

Full-Stack Application Development

• Build user-facing applications that enable interaction with AI-powered experiences.
• Develop modern frontend applications using frameworks such as React, Angular, Next.js, or comparable technologies.
• Create backend services, APIs, orchestration layers, and integration services using Python-based frameworks.
• Translate advanced AI capabilities into practical business applications and intuitive user experiences.
• Own solutions end-to-end from architecture through deployment and support.

Data & AI Infrastructure

• Build and maintain data ingestion, integration, and transformation pipelines.
• Develop and support retrieval-augmented generation (RAG) solutions and enterprise search capabilities.
• Design systems supporting context management, retrieval, memory, and personalisation.
• Integrate AI solutions with databases, APIs, analytics platforms, and enterprise applications.
• Ensure data quality, security, reliability, and scalability across AI systems.

LLM Engineering

• Integrate and orchestrate large language models within production environments.
• Design prompting strategies, retrieval approaches, tool-calling frameworks, and multi-step workflows.
• Build AI-powered capabilities including conversational assistants, document intelligence, semantic search, and workflow automation.
• Evaluate models, architectures, and AI platforms for performance, reliability, business fit, and cost efficiency.
• Establish monitoring and evaluation methodologies for production AI solutions.

Engineering Excellence

• Leverage AI-assisted development tools to improve engineering productivity while maintaining high code quality standards.
• Stay current with emerging AI frameworks, tooling, and industry best practices.
• Implement CI/CD, testing, observability, security, and production monitoring practices.
• Support reliable deployment and ongoing optimisation of AI-enabled applications.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
• 8+ years of professional software engineering experience.
• Strong full-stack development experience across frontend and backend technologies.
• Proven experience building and maintaining RESTful APIs and backend services.
• Experience working with data-intensive applications and enterprise integrations.
• Hands-on experience developing AI agents, autonomous workflows, or LLM-powered applications.
• Strong understanding of LLMs, RAG, tool usage, orchestration frameworks, and AI application architectures.
• Experience integrating AI systems with APIs, databases, enterprise platforms, and third-party services.
• Frontend experience with React, Angular, Next.js, or similar frameworks.
• Experience using AI-assisted development tools within software delivery workflows.
• Experience designing agent memory, retrieval, context, evaluation, or reasoning systems.
• Strong understanding of cloud-native application development and deployment.

Preferred Qualifications

• Experience with modern data-platform or lakehouse architectures.
• Experience deploying applications on public cloud platforms.
• Experience with CI/CD pipelines, infrastructure automation, and cloud operations.
• Experience working within agile software delivery environments.
• Experience building highly scalable enterprise applications.

What Success Looks Like

• Demonstrates an AI-first engineering mindset focused on intelligent workflows rather than simple AI integrations.
• Comfortable operating across software engineering, AI, data, and infrastructure domains.
• Balances innovation with reliability, observability, governance, and security.
• Strong product mindset with a focus on measurable business outcomes.
• Effective communicator who collaborates with technical and non-technical stakeholders.
• Thrives in fast-moving environments where requirements and technologies evolve rapidly.

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Customer Analytics Manager | 12-Month FTC | Up to £70k | Hybrid

A leading UK retail business is looking for a Customer Analytics Manager to join its established Customer Analytics function on a 12-month fixed-term contract.

You’ll be responsible for delivering customer insight across areas including customer behaviour, segmentation, lifecycle, retention and customer value, helping the wider business make more informed, data-driven decisions.

We’re looking for someone with:

• Strong experience in customer analytics / customer insight

• Excellent SQL and analytical skills

• Experience with segmentation, regression, clustering and predictive analytics

• Strong commercial and stakeholder management skills

• The ability to translate complex analysis into clear recommendations

This is a hands-on role with strong exposure to senior stakeholders and the opportunity to influence customer strategy across a large consumer business.

Package: Up to £70k + benefits
Contract: 12-month FTC
Location: Hybrid – 2/3 days per week in London

Interview process: Initial interview → Case study/presentation → Final stage.

Find out more and apply via the link below!

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Marketing & Customer Analyst

Up to £40,000 + Benefits | Hybrid Working – x2 days a week in London

We’re partnering with a growing analytics and customer insight consultancy looking to hire a Marketing & Customer Analyst to join their expanding team.

This is an excellent opportunity for an analytically-minded professional who enjoys turning data into meaningful commercial recommendations. You’ll work across a range of customer, CRM and marketing analytics projects, helping clients better understand customer behaviour, performance and growth opportunities.

What you’ll be doing:

• Analysing customer and marketing data to uncover actionable insights
• Building and developing dashboards and visualisations (Power BI preferred)
• Working with Python, Excel and large datasets to solve business problems
• Supporting customer segmentation, retention and loyalty projects
• Presenting findings and recommendations to both internal and external stakeholders
• Contributing to broader strategic consulting and insight projects

What we’re looking for:

• 2-4 years’ experience in an analytics, insight or customer data role
• Agency, consultancy or client-facing analytics experience preferred
• Strong Power BI and Excel skills
• Experience using Python for data analysis and manipulation
• A STEM-related degree or strong analytical academic background
• Excellent communication skills with the ability to translate data into clear business recommendations

Why apply?

• Diverse project work across customer analytics, CRM and marketing effectiveness
• Exposure to well-known consumer brands
• Opportunity to develop consulting and stakeholder management skills
• Collaborative, high-visibility team environment
• Flexible hybrid working arrangement

For more information, get in touch.

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Growth Analyst | Up to £80,000 | London (4 days office)

DTC Subscription Business

We are working with a fast-growing, venture-backed DTC subscription business in the consumer space, currently hiring a Growth Analyst to join their Acquisition and Product/Growth team.

The business is highly data-driven with analytics central to decision-making across Product, Marketing, and Finance. This is a commercially focused role where you will be expected to go beyond reporting and actively identify opportunities to improve acquisition, retention, and LTV.

The Role

You will take ownership of end-to-end growth analysis across the customer funnel, supporting experimentation and delivering insights that directly influence commercial decisions. The role sits in a fast-paced environment with highly analytical stakeholders.

Key Responsibilities

• Funnel analysis across acquisition, activation, retention and LTV
• Cohort, segmentation and customer lifecycle analysis
• Design and evaluation of A/B tests and experiments
• Build and maintain dashboards and KPI reporting
• Identify drivers of performance changes and growth opportunities
• Support marketing channel performance and optimisation
• Deliver actionable insights to senior stakeholders

Requirements

• Strong SQL skills and experience with a BI tool (Looker, Tableau, Power BI etc.)
• Experience in a consumer tech, subscription, marketplace or digital business
• Background in Growth, Product or Marketing Analytics
• Strong academic record with clear evidence of impact and progression
• Strong commercial mindset and stakeholder management skills
• Proactive, curious and comfortable working in ambiguity

Desirable

• Experience with A/B testing / experimentation
• Exposure to attribution or MMM
• Forecasting or opportunity sizing experience
• Python or advanced analytics skills

Process

• 30 min intro interview + 45 min founder interview (in-person)
• Take-home analysis task + SQL test (video interview)
• Final in-person interview focused on analytical thinking and execution

Find out more and apply via the link below!

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About the Role

This is a hands-on technical leadership role at the intersection of full-stack engineering and clinical AI. You will own the design and development of internal web portals, dashboards, and clinical tools used directly by clinical affairs staff – from report generation and patient communication to clinical decision support. You will work closely with the clinical affairs team, contribute to platform architecture, lead design reviews, and mentor junior engineers as the team grows.

This is not a back-end-only role – strong frontend skills are essential. You will be building the interfaces that clinicians use every day, and the quality of that experience matters.

What You’ll Own

• Design, build, and maintain internal clinical web portals and dashboards
• Lead development of LLM-powered tools for report generation, patient communication, and clinical decision support
• Partner closely with the clinical affairs team to translate workflows into effective technical solutions
• Contribute to platform architecture and participate in design reviews
• Mentor junior engineers and help set engineering standards as the team scales
• Ensure solutions meet the security, compliance, and reliability requirements of a regulated clinical environment

Required

• 3+ years of full-stack engineering experience
• Python – Django or similar backend framework
• Strong JavaScript/TypeScript and React or similar frontend framework
• API development, and system architecture skills
• Hands-on experience with LLMs
• Experience building internal web tooling
• Strong frontend skills

Strongly Preferred

• Production LLM, RAG, or prompt engineering experience in a clinical or regulated context
• Experience in regulated healthcare environment
• Exposure to biotech or similar regulated healthcare environments
• Kubernetes is helpful

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Lead Data Scientist
$140,000-$150,000
4 days/week in-office in NW Phoenix

Overview

A leading enterprise organisation is seeking a senior-level Data Scientist to lead the development, validation, and implementation of advanced quantitative models in a highly regulated environment. This role will serve as a technical leader, partnering with business and executive stakeholders to identify financial opportunities, quantify outcomes, and drive data-driven decision making.
The successful candidate will bring deep expertise in risk and financial modelling, strong statistical and mathematical foundations, and the ability to independently deliver complex analytics projects from concept through deployment and governance review.

Key Responsibilities

• Design, develop, validate, and monitor advanced predictive and risk models.
• Analyse large-scale financial, transactional, and customer datasets.
• Apply machine learning and statistical techniques to solve complex business problems.
• Translate model insights into measurable financial impact and business recommendations.
• Lead analytics initiatives from problem definition through implementation and performance tracking.
• Present technical findings and strategic recommendations to senior leadership and executive stakeholders.
• Support model governance activities, regulatory reviews, and external audit processes.
• Collaborate with cross-functional teams to ensure models are aligned with business objectives and compliance requirements.
• Provide technical guidance and mentorship to peers and junior team members.

Required Qualifications

• 8+ years of experience in Data Science, Quantitative Analytics, Risk Analytics, or a related discipline.
• Advanced proficiency in Python and SQL.
• Strong expertise in data modelling, statistical analysis, and quantitative problem solving.
• Experience developing and evaluating gradient boosting and other predictive modelling techniques.
• Proven ability to independently own and drive complex analytical projects.
• Exceptional communication and presentation skills, including experience presenting to executive audiences.
• Demonstrated experience defending models during audits, reviews, or governance assessments.
• Background in financial or risk modelling within a regulated industry.

Required Domain Experience

Candidates should have experience in one or more of the following areas:

• Credit risk modelling
• Financial forecasting and modelling
• Loss estimation and assessment
• Probability of Default (PD) modelling
• Risk scorecard development
• Payment and behavioural modelling
• Credit attribute modelling
• Banking, lending, consumer credit, mortgage, or credit bureau data
• Financial impact analysis
• Risk analytics within regulated financial institutions

Preferred Qualifications

• Bachelor’s degree in a quantitative discipline such as Mathematics, Statistics, Economics, Computer Science, Engineering, or a related field.
• Master’s degree in Data Science, Statistics, Applied Mathematics, Economics, or a similar quantitative discipline preferred.
• Advanced academic training with significant mathematical and statistical coursework.

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Lead Data Scientist
$140,000-$150,000
4 days/week on-site in Alpharetta

Overview

A leading enterprise organisation is seeking a senior-level Data Scientist to lead the development, validation, and implementation of advanced quantitative models in a highly regulated environment. This role will serve as a technical leader, partnering with business and executive stakeholders to identify financial opportunities, quantify outcomes, and drive data-driven decision making.
The successful candidate will bring deep expertise in risk and financial modelling, strong statistical and mathematical foundations, and the ability to independently deliver complex analytics projects from concept through deployment and governance review.

Key Responsibilities

• Design, develop, validate, and monitor advanced predictive and risk models.
• Analyse large-scale financial, transactional, and customer datasets.
• Apply machine learning and statistical techniques to solve complex business problems.
• Translate model insights into measurable financial impact and business recommendations.
• Lead analytics initiatives from problem definition through implementation and performance tracking.
• Present technical findings and strategic recommendations to senior leadership and executive stakeholders.
• Support model governance activities, regulatory reviews, and external audit processes.
• Collaborate with cross-functional teams to ensure models are aligned with business objectives and compliance requirements.
• Provide technical guidance and mentorship to peers and junior team members.

Required Qualifications

• 8+ years of experience in Data Science, Quantitative Analytics, Risk Analytics, or a related discipline.
• Advanced proficiency in Python and SQL.
• Strong expertise in data modelling, statistical analysis, and quantitative problem solving.
• Experience developing and evaluating gradient boosting and other predictive modelling techniques.
• Proven ability to independently own and drive complex analytical projects.
• Exceptional communication and presentation skills, including experience presenting to executive audiences.
• Demonstrated experience defending models during audits, reviews, or governance assessments.
• Background in financial or risk modelling within a regulated industry.

Required Domain Experience

Candidates should have experience in one or more of the following areas:

• Credit risk modelling
• Financial forecasting and modelling
• Loss estimation and assessment
• Probability of Default (PD) modelling
• Risk scorecard development
• Payment and behavioural modelling
• Credit attribute modelling
• Banking, lending, consumer credit, mortgage, or credit bureau data
• Financial impact analysis
• Risk analytics within regulated financial institutions

Preferred Qualifications

• Bachelor’s degree in a quantitative discipline such as Mathematics, Statistics, Economics, Computer Science, Engineering, or a related field.
• Master’s degree in Data Science, Statistics, Applied Mathematics, Economics, or a similar quantitative discipline preferred.
• Advanced academic training with significant mathematical and statistical coursework.

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