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AI Transformation Director
New York, NY (Hybrid) | $250,000 – $275,000 Base Salary + 20% Bonus
This is a rare opportunity to join a high-growth consulting business at the forefront of AI transformation. You will work directly with senior executives to help organisations identify where AI can create measurable commercial value, shape transformation strategies, and lead complex programmes that deliver tangible business outcomes.
The Company
They are a well-established innovation and transformation consultancy that partners with enterprise and mid-market organisations to solve complex business challenges. Their work sits at the intersection of strategy, transformation, and AI, helping clients move from identifying opportunities through to delivering real value.
With growing demand for AI transformation services, they are investing heavily in expanding their leadership team. This role offers significant visibility, autonomy, and the opportunity to influence both client outcomes and the future growth of the business.
The Role
As an AI Transformation Director, you will lead strategic AI transformation engagements from opportunity identification through to delivery.
Key responsibilities include:

• Leading AI transformation programmes for enterprise and mid-market clients
• Advising C-suite and senior leadership teams on AI strategy and value creation opportunities
• Defining business transformation roadmaps, operating model changes, and implementation plans
• Structuring and developing proposals, scopes of work, and client approaches
• Leading cross-functional consulting and delivery teams
• Acting as a senior strategic advisor across complex client engagements
• Identifying opportunities to expand client relationships and grow existing accounts
• Translating business objectives into practical AI-enabled solutions that deliver measurable impact
• Supporting commercial growth through engagement shaping and proposal development

Your Skills & Experience
You will bring a strong consulting background combined with experience helping organisations navigate strategic transformation initiatives.
Key requirements include:

• Experience within a leading strategy consulting firm or high-quality transformation consultancy
• Strong client-facing consulting and executive stakeholder management experience
• Expertise in business transformation, growth strategy, operating model design, or digital transformation
• Experience helping organisations identify and realise value from AI initiatives
• Ability to structure complex problems and develop practical transformation strategies
• Experience leading large-scale consulting engagements from strategy through execution
• Strong commercial awareness, including engagement shaping, proposal development, and account growth
• Ability to operate effectively in ambiguous environments and influence senior decision-makers
• Track record of delivering measurable business outcomes for clients

What They Offer

• Base salary of $250,000 with flexibility up to $275,000 for exceptional candidates
• 20% annual bonus
• Hybrid working model based in New York
• Opportunity to work directly with senior executive stakeholders
• High levels of autonomy and ownership within a growing AI consulting practice
• Clear progression opportunities as the business continues to scale
• Potential consideration for candidates forfeiting outstanding bonus or incentive payments

How to Apply
If you have a consulting-led background in business transformation and AI strategy, and are excited by the opportunity to help organisations unlock measurable value through AI, please apply today.

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PRICING LEAD

SALARY BETWEEN £80,000-£90,000

LONDON

HYBRID WORKING (ONCE A WEEK IN-OFFICE, BUT CAN FLEX TO ONCE A MONTH)

Harnham are working with a specialist insurance provider that is continuing to invest in its pricing and analytics capabilities. This is an exciting opportunity for an experienced pricing professional to take ownership of a broad remit spanning pricing, analytics and fraud within a growing business.

THE COMPANY

This specialist insurance provider has undergone significant transformation in recent years, investing heavily in its pricing, underwriting and analytics capabilities. Operating within the personal lines insurance market, the business has built a strong reputation for combining technical excellence with a modern, technology-led approach. With a lean and highly capable team, the organisation offers an agile environment where employees have the opportunity to make a visible impact and work closely with senior decision-makers.

THE ROLE

As a Pricing Lead, you will take ownership of pricing capability across multiple products. Working closely with senior stakeholders, you will play a key role in shaping pricing strategy, developing analytical frameworks and supporting wider business growth.

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

• Leading the development and enhancement of pricing models and rating strategies.
• Building and maintaining pricing processes, governance frameworks and monitoring capabilities.
• Delivering portfolio analytics and performance insights to support commercial decision-making.
• Developing fraud analytics capabilities and integrating insights into pricing and underwriting processes.
• Partnering with underwriting, claims, data and technology teams to deliver business change.

SKILLS AND EXPERIENCE

The successful Pricing Lead will have the following skills and experience:

• 5+ years’ experience within personal lines pricing, ideally within motor insurance.
• Strong Python skills with experience building pricing models and analytical solutions.
• Solid understanding of pricing methodologies, including statistical and machine learning techniques.
• Experience working with rating engines and implementing pricing changes.
• Ability to communicate technical findings to both technical and non-technical stakeholders.
• Comfortable working independently within a fast-paced, evolving environment.
• Strong academic background in a quantitative discipline.

BENEFITS

The successful Pricing Lead will receive a salary up to £90,000 as well as a discretionary bonus.

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AI Engineer
London (Hybrid, 3 days per week)

This is an opportunity to join a newly formed AI function at a pivotal stage of growth. You’ll work on high-impact AI initiatives across machine learning, Generative AI and Agentic AI, helping to shape how AI is adopted and scaled across a major organisation.

The Company
Our client is investing significantly in AI as part of a large-scale transformation programme. Operating through a central AI Centre of Excellence, they are building scalable, production-ready AI solutions that deliver measurable business value. This is a chance to join early, influence standards and best practice, and play a key role in a growing AI engineering team.

The Role
You will:

• Design, build and deploy AI and machine learning solutions from concept to production
• Develop applications using LLMs, Generative AI and Agentic AI frameworks
• Deliver predictive, optimisation and automation use cases
• Build robust MLOps and LLMOps processes, including monitoring and evaluation
• Work closely with engineers, data scientists, product teams and business stakeholders
• Help establish AI engineering standards, governance and responsible AI practices
• Contribute to the long-term technical direction of the AI team

Your Skills & Experience

• Strong Python and software engineering background
• Commercial experience delivering machine learning models into production
• Hands-on experience with GenAI, LLMs and AI application development
• Knowledge of MLOps, LLMOps, CI/CD and containerisation
• Experience with cloud platforms, ideally Azure
• Understanding of model evaluation, monitoring and responsible AI
• Strong communication skills with the ability to translate business requirements into technical solutions

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About the Role

We are partnering with a Fortune 100 financial institution on a Staff Machine Learning Engineer opportunity within its enterprise AI organization. The team is responsible for developing and scaling LLM-powered products and reusable AI services that support AI adoption across the organization.

The firm’s enterprise LLM platform is used by more than 320,000 employees, with AI applications spanning chatbots, text-to-code, database interactions, workflow automation, and AI agents.

What You’ll Do

• Build and optimize scalable LLM-based products and AI applications.
• Combine large-scale data assets with cutting-edge AI, including LLMs and multimodal LLMs.
• Bridge scientific research and software engineering, taking ideas from research into production.
• Design and deliver production architectures in collaboration with Cloud and SRE teams.
• Build reusable backend APIs that allow other teams to leverage AI capabilities within their own products.
• Prototype, code, and deploy ML solutions independently.
• Design systems capable of handling large volumes of requests while maintaining performance and reliability.
• Work across applications including:
  • Chatbots
  • Text-to-code
  • SQL/database interactions
  • Workflow automation
  • AI agents

Scale & Impact

• Enterprise LLM platform used by 320,000+ employees.
• Platform enables employees to accelerate their ML adoption, going from 0-80% in their ML journey in approximately three days instead of months.
• First-week releases can produce tools used by 100,000 employees.
• Strong emphasis on adoption, productivity, and measurable enterprise impact.

What We’re Looking For

• Strong production Machine Learning Engineering background.
• Deep understanding of ML/AI foundational models and API-based LLM integrations.
• Experience building and deploying production ML systems independently.
• Strong software engineering and system design fundamentals.
• Experience designing scalable systems and production architectures.
• Ability to bridge research, ML engineering, and production software development.
• Experience working with cloud and infrastructure teams.
• Strong analytical and problem-solving skills.
• Ability to work independently and move quickly from problem definition to production solution.

Compensation & Location

• Location: New York City or Palo Alto
• Work Arrangement: 5 days per week onsite
• Compensation: Up to $650K total compensation, depending on level and experience.

Why This Opportunity

This is an opportunity to work on enterprise-scale Generative AI with direct, measurable impact across a global organization. The team is focused on building production AI systems that can reach hundreds of thousands of users and meaningfully change how employees work.

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ML Scientist

$250,000-$280,000

Overview

A fast-growing technology-driven life sciences organization is seeking a highly skilled Machine Learning Research Scientist to help build and advance large-scale foundation models that integrate complex biological data. This role sits at the intersection of artificial intelligence, machine learning research, and scientific discovery.
The successful candidate will work with an interdisciplinary team of researchers, engineers, and domain specialists to develop novel modelling approaches, evaluate emerging technologies, and translate cutting-edge AI research into real-world impact. The position offers significant ownership, opportunities for publication and technical leadership, and exposure to large-scale machine learning systems.

Key Responsibilities

• Design, implement, train, and optimise foundation models that integrate diverse biological and scientific datasets.
• Develop benchmarking frameworks and evaluation methodologies for large-scale machine learning models.
• Assess state-of-the-art open-source models and identify opportunities for improvement or adoption.
• Lead research initiatives from concept through experimentation, analysis, and communication of findings.
• Collaborate closely with technical and scientific stakeholders to translate complex research outcomes into actionable insights.
• Contribute to technical publications, presentations, and engagement with the broader research community.
• Evaluate the use of large language models and related technologies to enhance research workflows and model capabilities.
• Rapidly prototype and test novel ideas, prioritising high-impact experiments and research directions.
• Support the development of scalable machine learning infrastructure for training and deploying advanced models.

Required Qualifications

• Strong publication record and/or presentations at leading machine learning conferences or equivalent research venues.
• Proven experience developing machine learning models and datasets using PyTorch or similar deep learning frameworks.
• Deep understanding of modern machine learning architectures and self-supervised learning techniques.
• Expertise in areas such as representation learning, generative modelling, diffusion methods, latent variable models, or autoregressive architectures.
• Experience training, tuning, and evaluating large-scale machine learning models.
• Familiarity with distributed training environments and scalable machine learning systems.
• Experience with tools and frameworks used for large-scale model development, orchestration, and experimentation.

Preferred Qualifications

• Experience working with multimodal datasets.
• Background in scientific machine learning, computational biology, healthcare AI, or related domains.
• Demonstrated ability to communicate technical research to both technical and non-technical audiences.
• Experience collaborating across disciplines in research-intensive environments.

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AI Engineer
London (Hybrid – 3x a week)

The Company
They are a large, data-driven organisation investing heavily in artificial intelligence and advanced analytics. Their AI team is focused on building innovative solutions that improve business operations, enhance customer experiences, and drive measurable commercial value. With access to large and complex datasets, they offer an environment where experimentation, collaboration, and technical excellence are encouraged.

The Role

• Design, build and deploy scalable AI and machine learning solutions, taking projects from concept through to production.
• Develop AI-powered applications using Generative AI, Large Language Models and orchestration frameworks.
• Write high-quality Python code and contribute to cloud-native applications and services.
• Apply MLOps best practices, including CI/CD, containerisation, monitoring and observability.
• Partner with data scientists, engineers and business stakeholders to translate business challenges into impactful AI solutions.
• Monitor, evaluate and improve deployed models while ensuring responsible, secure and reliable AI deployment.

Your Skills & Experience

• Strong commercial experience in AI engineering, machine learning engineering or software engineering with applied AI.
• Proven experience building and deploying Generative AI applications using LLMs and orchestration frameworks.
• Strong Python programming skills and understanding of modern backend architectures.
• Experience working with cloud platforms and production-grade AI systems.
• Knowledge of MLOps, CI/CD, containerisation and model monitoring.
• Experience building data pipelines for model training, fine-tuning and inference.
• Solid grounding in machine learning, statistics and model evaluation techniques.
• Strong communication skills with the ability to engage technical and non-technical stakeholders.
• Commitment to responsible and ethical AI development.

What They Offer

• Competitive salary and comprehensive benefits package.
• Hybrid working model.
• Exposure to large-scale AI and machine learning projects.
• Opportunity to shape the direction of a growing AI capability.
• Ongoing professional development and clear career progression.
• Collaborative environment working alongside experienced AI, data and engineering professionals.

How to Apply
If you’re an AI Engineer looking to build and deploy innovative AI solutions in a high-impact environment, please apply today to learn more about this opportunity.

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Chief Scientist

$300,000- $350,000

Overview

A mission-driven research organisation is seeking a Chief Scientist to lead its scientific strategy, research operations, and interdisciplinary research teams. Reporting directly to the Chief Executive Officer and serving as a member of the executive leadership team, this individual will oversee multiple research functions and ensure alignment between scientific objectives, organisational priorities, and long-term impact.
This role focuses on building and leading a high-performing research organisation rather than serving as an individual contributor. The successful candidate will bring deep expertise in artificial intelligence, substantial leadership experience, and the ability to integrate technical and scientific disciplines into a cohesive research strategy.

Key Responsibilities

Scientific Leadership & Strategy

• Define and oversee a multi-year scientific roadmap aligned with organisational mission and objectives.
• Ensure close collaboration between AI-focused research and domain science teams to drive meaningful scientific outcomes.
• Maintain high standards of scientific rigor, reproducibility, and research integrity.
• Monitor relevant developments in machine learning, computational science, behavioural research, and related disciplines, translating insights into strategic opportunities.

Research Organisation Leadership

• Lead, mentor, and develop senior research leaders and multidisciplinary teams.
• Design organisational structures, staffing plans, and growth strategies to support research priorities.
• Recruit and retain exceptional scientific and technical talent, particularly for senior leadership positions.
• Partner with programme and operational leaders to prioritise initiatives, allocate resources, and ensure effective execution.
• Foster an inclusive, collaborative, and high-performing research culture.

Executive Leadership

• Serve as a strategic partner to executive leadership on organisational direction and long-term planning.
• Align research priorities with fundraising, communications, and organisational initiatives.
• Present research strategy, progress, and key decisions to leadership, funders, boards, and external stakeholders.
• Support external communications by ensuring scientific findings and organisational priorities are accurately represented.

Financial Management

• Own research budget planning and spending within approved parameters.
• Develop and manage multi-year research budget forecasts in partnership with organisational leadership.
• Monitor expenditures and proactively identify significant budgetary changes or risks.

External Engagement

• Represent the organisation at scientific, industry, and professional events.
• Develop partnerships with academic institutions, government organisations, nonprofits, and research collaborators.
• Contribute to publications, thought leadership, and public-facing scientific communications.
• Expand external research networks through fellowships, internships, and academic outreach programmes.

Culture & Ethical Leadership

• Promote cross-functional collaboration and transparent knowledge sharing.
• Create an environment that values respect, inclusion, and diverse perspectives.
• Encourage participation from researchers at all levels in scientific planning and decision-making.
• Uphold strong ethical standards in research design, data usage, interpretation, and communication.

Required Qualifications

Education

• PhD in Machine Learning, Computer Science, Electrical Engineering, Computational Biology, or a closely related discipline.
• Strong scientific credibility and research accomplishments, though an active publication record is not required.

Experience

• 15+ years of experience spanning AI research, large-scale AI implementation, or a combination of both.
• Demonstrated success leading research organisations, technical teams, or advanced AI programmes.
• Significant experience evaluating research quality and managing senior researchers or technical leaders.
• Experience building teams, setting strategic direction, and maintaining scientific standards.
• Strong professional network within the AI research and technology community.
• Ability to recruit and develop senior-level scientific talent.

Technical Expertise

• Deep understanding of modern AI and machine learning methodologies.
• Familiarity with foundation models, large-scale model training, and production-scale AI systems.
• Experience assessing research quality across interdisciplinary environments.
• Understanding of quantitative scientific research methods and data-driven experimentation.

Leadership Skills

• Proven ability to lead complex, multidisciplinary research organisations.
• Strong organisational judgement and strategic decision-making skills.
• Excellent communication skills with executive, scientific, funding, and public audiences.
• Ability to bridge different research cultures and disciplines effectively.
• Passion for mission-oriented scientific research and long-term impact.

Preferred Qualifications

• Experience working in both academic and commercial research environments.
• Background applying AI to scientific or natural-world research domains.
• Familiarity with machine learning for audio, speech, computer vision, or related data modalities.
• Experience in nonprofit, research institute, mission-driven, or field-based scientific organisations.
• Knowledge of responsible AI frameworks and ethical research practices.

Work Model / Reporting Structure

• Reports directly to the Chief Executive Officer.
• Serves as a member of the executive leadership team.
• Oversees senior leaders responsible for research, scientific programmes, and research infrastructure.
• Holds broad authority over scientific direction, research priorities, and organisational research strategy.
• Supported by operational, finance, programme management, legal, and human resources functions.

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Senior Machine Learning Scientist

London (Remote)

The Company
They are an innovative technology business leveraging advanced machine learning, natural language processing, and Generative AI to help organisations extract meaningful insights from large volumes of unstructured data. Their environment combines research, experimentation, and product development, giving technical teams the opportunity to work on real-world AI challenges while delivering measurable business impact.

The Role

• Train, evaluate and optimise machine learning models and agentic AI systems, owning experimentation from end to end.
• Build and enhance LLM-powered solutions including retrieval pipelines, reranking systems, intelligent agents and automated taxonomy generation.
• Design robust evaluation frameworks, define metrics and benchmark model performance across a range of NLP applications.
• Improve semantic search and retrieval capabilities using advanced machine learning and information retrieval techniques.
• Partner with engineering teams to deploy and monitor production-ready machine learning solutions.
• Collaborate with product and business stakeholders to deliver impactful AI solutions while mentoring colleagues and promoting technical best practice.

Your Skills & Experience

• Strong commercial experience with transformer architectures and modern NLP techniques.
• Advanced Python and PyTorch skills, including custom model training and optimisation.
• Experience fine-tuning, evaluating and deploying large language models.
• Experience working with large-scale text datasets and real-world machine learning problems.
• Solid grounding in statistics and classical machine learning.
• Hands-on experience developing Generative AI and agentic AI solutions.
• Excellent communication skills with the ability to engage technical and non-technical stakeholders.

What They Offer

• Competitive salary and benefits package.
• Hybrid working model.
• Opportunity to work on cutting-edge AI and machine learning products.
• Strong career progression within a growing Data Science and AI function.
• Collaborative, research-driven culture with exposure to the latest advancements in machine learning.

How to Apply
To find out more about this Senior Machine Learning Scientist opportunity, please submit your application today.

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Senior Manager, Full-Stack Engineering

$190,000-$210,000

4 days/week on-site in Houston or Austin

Overview

A growing technology-driven organisation is seeking a Senior Manager, Full-Stack AI Engineering to lead a small team of engineers delivering AI-powered software solutions. This is a highly hands-on leadership position, with the majority of time spent contributing directly to architecture, development, and delivery while also managing and developing engineers.
The ideal candidate brings a strong full-stack engineering background and has successfully transitioned into AI-focused application development. This individual should have practical experience deploying large language model (LLM) solutions, generative AI capabilities, retrieval-augmented systems, agent-based architectures, and AI-assisted software development workflows in production environments.
This role partners closely with product, data, and AI stakeholders to deliver enterprise-scale applications while establishing engineering excellence across the team.

Key Responsibilities

Technical Leadership & Delivery

• Lead the design, development, and deployment of production-grade AI-enabled applications.
• Contribute directly to coding, architecture, solution design, and technical delivery across multiple initiatives.
• Build and support end-to-end solutions spanning frontend applications, backend services, APIs, data integration pipelines, and AI-powered features.
• Provide technical direction on AI integration patterns, system architecture, cloud-native solutions, and software engineering best practices.
• Conduct architecture reviews, code reviews, and technical design discussions.
• Ensure scalability, maintainability, security, and operational excellence across delivered solutions.

Team Management

• Manage and mentor a team of software engineers across multiple workstreams.
• Conduct performance reviews, regular coaching sessions, and career development planning.
• Foster a culture of accountability, collaboration, continuous learning, and delivery excellence.
• Participate in hiring, onboarding, and talent development activities.

Engineering Standards & Quality

• Establish and enforce standards for coding, testing, documentation, security, and release management.
• Promote responsible use of AI-assisted development tools and establish best practices for their adoption.
• Evaluate emerging engineering and AI development tools to improve team effectiveness and software quality.
• Ensure AI-generated code meets the same standards as manually authored code.

Cross-Functional Collaboration

• Partner with product leaders, data teams, AI specialists, and business stakeholders to prioritise and deliver solutions.
• Communicate technical risks, dependencies, and delivery expectations effectively.
• Contribute to planning, estimation, and process improvement initiatives.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical discipline.
• 10+ years of software engineering experience with substantial full-stack development expertise.
• 5+ years of engineering leadership or people management experience.
• Demonstrated experience hiring, mentoring, and developing software engineering talent.
• Strong experience with modern full-stack technologies, including:
  • Frontend frameworks such as React or Angular.
  • Backend development using Java, Python, Go, or similar languages.
  • Python frameworks such as FastAPI, Django, or Flask.
• Experience delivering AI-enabled or data-intensive applications in production environments.
• Practical experience integrating LLMs, generative AI solutions, AI workflows, or related technologies into software products.
• Experience defining engineering standards covering code quality, testing, documentation, and security.
• Experience implementing and governing AI-assisted coding workflows using tools such as Claude Code, Codex, Augment Code, or comparable platforms.
• Strong understanding of CI/CD, cloud-native architectures, deployment automation, and infrastructure-as-code.
• Experience managing multiple projects or delivery workstreams simultaneously.
• Ability to assess architecture quality, coding standards, technical complexity, and delivery risk.
• Excellent communication and stakeholder management skills.

Preferred Qualifications

• Experience building production solutions using retrieval-augmented generation (RAG), agent-based AI frameworks, and LLM-powered applications.
• Experience with modern cloud platforms, particularly AWS.
• Experience working with large-scale data platforms, lakehouse environments, or analytics ecosystems.
• Experience partnering with data scientists, ML engineers, and product teams in agile delivery environments.
• Prior experience in startup, scale-up, or small-to-mid-sized engineering environments.
• Background leading highly technical teams while remaining an active individual contributor.

Work Model / Location / Engagement Details

• Full-time permanent position.
• Remote-flexible within commuting distance of a major office location in the Southern United States.
• Candidates must reside within approximately 50 miles of the designated office region.
• In-office attendance required approximately 4 days per month.
• Occasional travel expected (approximately 20% to 30%).
• Compensation up to $210,000 base salary plus target bonus of 25%.

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Senior Machine Learning Engineer

$140,000-$190,000

Overview
A growing healthcare-focused technology organisation is seeking a Senior Machine Learning Engineer to help expand and support enterprise AI and machine learning capabilities. This role combines machine learning engineering, MLOps, cloud infrastructure, and generative AI operations.
The ideal candidate has extensive experience deploying, monitoring, and scaling production machine learning systems and is comfortable supporting both traditional ML models and modern large language model (LLM) applications. This position is focused on operational excellence, reliability, scalability, and measurable business outcomes rather than research.
Key Responsibilities

• Machine Learning Engineering & Platform Development
• Design, build, and maintain production-grade machine learning systems.
• Deploy and support machine learning models in live environments.
• Develop scalable training and inference workflows.
• Improve system reliability, performance, and operational efficiency.
• Partner with data science teams to productionise models and analytics solutions.
• MLOps & Infrastructure
• Develop and maintain feature engineering pipelines.
• Build and enhance workflow orchestration solutions.
• Establish best practices for model deployment and lifecycle management.
• Implement monitoring, observability, and alerting frameworks.
• Support model governance and operational compliance requirements.
• Generative AI & LLM Operations
• Deploy and maintain applications powered by large language models.
• Monitor model performance, quality, and reliability.
• Optimise prompts, inference processes, and operational workflows.
• Support cloud-hosted foundation model services.
• Implement improvements that enhance model effectiveness and user experience.
• Business Impact
• Contribute to predictive and decision-support solutions within healthcare and life sciences domains.
• Support projects involving optimisation, forecasting, classification, and recommendation systems.
• Deliver scalable solutions that create measurable value for end users and stakeholders.

Required Qualifications

• Technical Skills
• Strong Python development experience.
• Advanced SQL proficiency.
• Hands-on experience with AWS cloud services.
• Experience with machine learning platforms such as SageMaker.
• Experience using cloud-based LLM and foundation model services.
• DBT experience.
• Workflow orchestration experience with Prefect or similar platforms such as Airflow.
• Experience
• Approximately 6+ years of Machine Learning Engineering experience.
• Proven experience deploying machine learning models into production.
• Experience supporting model training and inference workloads.
• Strong model monitoring and observability experience.
• Ownership of MLOps processes and production ML environments.
• Experience designing and maintaining feature engineering pipelines.
• Infrastructure-focused engineering mindset with strong software engineering practices.
• Healthcare industry experience is required, including familiarity with:
• Regulated environments.
• Compliance and security requirements.
• Model governance practices.
• Responsible AI considerations, including fairness and bias mitigation.
• Preferred Qualifications
• Experience building ML-powered products used by external customers.
• Experience supporting models after deployment in production environments.
• Exposure to both traditional machine learning and LLM-based applications.
• Strong communication and stakeholder management skills.
• Demonstrated ability to deliver measurable business results through machine learning solutions.

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Pricing Lead
Remote based within UK
£80,000 to £90,000

This is an excellent opportunity for a Pricing Lead to join a growing insurance business where pricing plays a central role in commercial decision-making. You’ll work in a highly visible position with the freedom to shape processes, influence strategy, and take ownership of key pricing capability across the organisation.

The Company
They are a specialist insurer operating within the UK personal lines market. With a modern, technology-driven approach and a strong focus on analytics, they have continued to grow while maintaining a lean and highly capable team. The business values innovation, autonomy, and collaboration, giving employees direct exposure to senior decision-makers and strategic initiatives.

The Role

• Own and develop pricing models, methodologies, and rating approaches across the portfolio.
• Lead enhancements to pricing processes and pricing infrastructure.
• Use Python to develop, refine, and monitor pricing models.
• Support rating engine development and deployment.
• Deliver analytics across pricing performance, underwriting, and portfolio management.
• Develop fraud analytics capabilities and integrate insights into pricing decisions.
• Partner with senior stakeholders to translate technical findings into commercial recommendations.
• Collaborate with teams across underwriting, technology, and the wider business.
• Help shape the future direction of pricing capability as the organisation continues to grow.

Your Skills & Experience

• Strong commercial experience in personal lines pricing, ideally motor insurance.
• Proven pricing modelling experience and understanding of rating methodologies.
• Strong Python skills for analytics and model development.
• Knowledge of pricing governance and the UK insurance market.
• Ability to work independently, influence stakeholders, and communicate technical findings clearly.
• Experience with fraud analytics or rating engine deployment is advantageous.

What They Offer

• Salary of £80,000 to £90,000.
• Annual bonus scheme.
• Flexible hybrid working with occasional meet-ups in London.
• Exposure to senior leadership and strategic business decisions.
• Broad remit spanning pricing, analytics, and fraud.
• Opportunity to shape a growing function and develop your career in a high-impact environment.
• Private medical insurance, life assurance, and generous holiday allowance.

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Product Analyst
£60,000 – £70,000 + benefits
Hybrid – Manchester (3x days per week)

This is an opportunity to join a highly regarded digital business that reaches millions of consumers every week. Sitting within a cross functional product environment, you will use data to shape customer experiences, influence product strategy, and drive measurable business outcomes. You will take ownership of key analytics initiatives while helping to develop best practice across a growing analytics community.

The Company
They are a leading consumer focused digital organisation with a strong technology and data driven culture. Their platform supports millions of users, helping customers research, compare, and make informed purchasing decisions.
Data plays a central role in decision making across the business, and analytics is deeply embedded within product development. They offer a collaborative environment where analysts work closely with Product, Engineering, Design, and Research teams to solve complex customer challenges.

The Role
As a Senior Data Analyst, you will:

• Partner with product teams to define success metrics and measurement frameworks
• Establish robust governance, monitoring, and reporting standards for key product areas
• Design and develop data products in collaboration with data and engineering teams
• Drive improvements to tracking and measurement capabilities across digital products
• Lead experimentation and A/B testing programmes, providing actionable recommendations
• Support product discovery by working alongside Design and User Research teams
• Influence senior stakeholders through clear, evidence based insights
• Identify opportunities to improve customer journeys, engagement, and product performance
• Mentor and support other analysts within the wider analytics community
• Contribute to the development of analytics frameworks, standards, and best practices

Your Skills & Experience

• Strong commercial experience within consumer facing digital product environments
• Experience analysing complex customer journeys and behavioural data
• Knowledge of experimentation methodologies and statistical inference techniques
• Familiarity with product analytics and user behaviour tracking tools, such as Google Analytics or similar platforms
• Advanced SQL skills and working knowledge of Python
• Understanding of ETL processes and core data engineering concepts
• Ability to translate complex analysis into clear business recommendations
• Experience delivering analytics projects within cross functional teams
• Proven capability in mentoring, coaching, or leading analysts
• Strong stakeholder management and communication skills

What They Offer

• Salary of £50,000 to £70,000
• Annual equity award equivalent to 10% of salary
• Hybrid working model with regular collaboration in the office
• Generous annual leave allowance plus bank holidays
• Competitive pension scheme
• Private medical insurance and wellbeing support services
• Enhanced family friendly benefits
• Additional savings and share scheme options
• Clear opportunities to influence strategy and progress your analytics career within a mature data environment

How to Apply
If you are an experienced Senior Data Analyst looking to make an impact in a product led, data driven organisation, please apply with your CV to discuss the opportunity further.

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