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Lead Data Scientist

$140,000-$150,000 + 10% bonus

Overview

A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.

Key Responsibilities

Project Leadership & Stakeholder Management

• Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
• Independently lead projects from problem definition through deployment and performance monitoring.
• Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
• Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
• Present findings and recommendations to leadership teams, including executive audiences.

Advanced Analytics & Data Science

• Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
• Design segmentation frameworks using clustering and classification techniques.
• Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
• Identify patterns, root causes, and opportunities through large-scale data analysis.
• Develop innovative analytical approaches to improve insight generation and operational effectiveness.
• Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.

Data Management & Process Improvement

• Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
• Establish data quality standards and controls to improve accuracy and consistency.
• Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
• Monitor and assess the ongoing performance of implemented analytical solutions.

Executive Communication

• Translate complex analytical findings into actionable business recommendations.
• Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.

Required Qualifications

• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
• 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
• 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
• 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
• Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
• Demonstrated experience analysing large structured and unstructured datasets.
• Experience presenting analytical insights to executive audiences and influencing strategic decisions.
• Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
• Strong project management, prioritisation, and multitasking skills.
• Proven ability to work independently in a fast-paced, evolving environment.
• Experience sourcing, validating, and integrating data from multiple systems and platforms.

Preferred Qualifications

• Master’s degree in a quantitative discipline.
• Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
• Experience using consumer, credit, demographic, or third-party external datasets.
• Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
• Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
• Familiarity with model risk management frameworks and third-party model review processes.
• Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
• Experience with modern data warehouse technologies.

To Apply for this Job Click Here

To Apply for this Job Click Here

Lead Data Scientist

$140,000-$150,000 + 10% bonus

Overview

A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.

Key Responsibilities

Project Leadership & Stakeholder Management

• Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
• Independently lead projects from problem definition through deployment and performance monitoring.
• Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
• Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
• Present findings and recommendations to leadership teams, including executive audiences.

Advanced Analytics & Data Science

• Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
• Design segmentation frameworks using clustering and classification techniques.
• Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
• Identify patterns, root causes, and opportunities through large-scale data analysis.
• Develop innovative analytical approaches to improve insight generation and operational effectiveness.
• Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.

Data Management & Process Improvement

• Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
• Establish data quality standards and controls to improve accuracy and consistency.
• Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
• Monitor and assess the ongoing performance of implemented analytical solutions.

Executive Communication

• Translate complex analytical findings into actionable business recommendations.
• Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.

Required Qualifications

• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
• 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
• 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
• 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
• Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
• Demonstrated experience analysing large structured and unstructured datasets.
• Experience presenting analytical insights to executive audiences and influencing strategic decisions.
• Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
• Strong project management, prioritisation, and multitasking skills.
• Proven ability to work independently in a fast-paced, evolving environment.
• Experience sourcing, validating, and integrating data from multiple systems and platforms.

Preferred Qualifications

• Master’s degree in a quantitative discipline.
• Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
• Experience using consumer, credit, demographic, or third-party external datasets.
• Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
• Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
• Familiarity with model risk management frameworks and third-party model review processes.
• Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
• Experience with modern data warehouse technologies.

To Apply for this Job Click Here

To Apply for this Job Click Here

Lead Data Scientist

$140,000-$150,000 + 10% bonus

Overview

A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.

Key Responsibilities

Project Leadership & Stakeholder Management

• Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
• Independently lead projects from problem definition through deployment and performance monitoring.
• Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
• Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
• Present findings and recommendations to leadership teams, including executive audiences.

Advanced Analytics & Data Science

• Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
• Design segmentation frameworks using clustering and classification techniques.
• Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
• Identify patterns, root causes, and opportunities through large-scale data analysis.
• Develop innovative analytical approaches to improve insight generation and operational effectiveness.
• Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.

Data Management & Process Improvement

• Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
• Establish data quality standards and controls to improve accuracy and consistency.
• Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
• Monitor and assess the ongoing performance of implemented analytical solutions.

Executive Communication

• Translate complex analytical findings into actionable business recommendations.
• Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.

Required Qualifications

• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
• 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
• 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
• 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
• Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
• Demonstrated experience analysing large structured and unstructured datasets.
• Experience presenting analytical insights to executive audiences and influencing strategic decisions.
• Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
• Strong project management, prioritisation, and multitasking skills.
• Proven ability to work independently in a fast-paced, evolving environment.
• Experience sourcing, validating, and integrating data from multiple systems and platforms.

Preferred Qualifications

• Master’s degree in a quantitative discipline.
• Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
• Experience using consumer, credit, demographic, or third-party external datasets.
• Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
• Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
• Familiarity with model risk management frameworks and third-party model review processes.
• Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
• Experience with modern data warehouse technologies.

To Apply for this Job Click Here

To Apply for this Job Click Here

DATA SCIENTIST, DECISION SCIENCES

London OR Cossington (Hybrid)

THE COMPANY
A data-driven consumer business with a large and engaged customer base is seeking a Data Scientist to join their Decision Sciences team. They are investing heavily in advanced analytics and machine learning, with data playing a central role in strategic decision-making across the organisation. You’ll work in a collaborative environment alongside analytics, marketing, and commercial stakeholders, delivering solutions that have a tangible impact on customer outcomes.

THE ROLE

• Build and develop machine learning models focused on customer retention, churn prediction, and customer lifetime value
• Evaluate and improve existing modelling pipelines to increase accuracy and commercial impact
• Partner with CRM and marketing teams to translate model outputs into actionable retention strategies
• Develop forecasting and marketing effectiveness models to support business planning and decision-making
• Design, analyse, and interpret A/B tests and experimentation frameworks
• Deliver insight through deep-dive analysis, dashboards, and clear communication to stakeholders

YOUR SKILLS & EXPERIENCE

• Strong commercial experience as a Data Scientist within marketing, ecommerce, customer, loyalty, or membership environments
• Advanced Python and SQL skills, with experience working in modern data environments
• Strong understanding of statistical modelling, experimentation, and causal inference
• Experience building and deploying predictive machine learning models
• Ability to communicate technical findings to non-technical audiences
• Experience working closely with CRM or lifecycle marketing teams is advantageous

WHAT THEY OFFER

• Competitive salary plus bonus
• Hybrid working and flexible hours
• Private healthcare and enhanced pension package
• Additional annual leave and wellbeing benefits
• Ongoing learning and development opportunities
• Clear career progression within a growing data team

HOW TO APPLY
To find out more about this Data Scientist, Decision Sciences opportunity, please submit your CV for consideration.

To Apply for this Job Click Here

To Apply for this Job Click Here

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.

To Apply for this Job Click Here

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Data Scientist

Knowsley – 3 days a week

The Company
They are a well established UK retail business undergoing a broader data and AI transformation. The organisation is investing in building a modern Data Science capability to support decision making across commercial and customer functions. Their culture is practical, collaborative and delivery focused, with an emphasis on creating value quickly rather than over engineering solutions. Data is increasingly central to their strategy, particularly with the launch of a new customer loyalty programme.

The Role
You will work closely with the Data Science Lead and a small but growing team to develop and productionise machine learning solutions.

• Build and deploy models that support customer and commercial decision making
• Work on use cases such as customer segmentation, lifetime value modelling and demand forecasting
• Contribute to the development of a scalable Data Science platform
• Collaborate with data engineers, analysts and business stakeholders
• Translate business problems into data science solutions and clearly communicate outputs
• Support the expansion of existing models into broader production use

Your Skills and Experience

• Strong commercial experience in Data Science using Python
• Solid SQL skills and experience working with large datasets
• End to end experience delivering Data Science solutions from problem definition through to deployment
• Experience building and validating machine learning models
• Ability to communicate insights clearly to non technical audiences
• A practical, business focused approach to problem solving

What They Offer

• Hybrid working with three days per week in Knowsley
• Opportunity to shape and influence a growing Data Science function
• Exposure to end to end project work with real business impact
• A collaborative environment focused on learning and delivery

How to Apply
Apply now to learn more about this Data Scientist opportunity and the impact you can make within a growing data driven environment.

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Lead Data Scientist

London – 4x a week

The Company
They are a fast-growing technology organisation that helps businesses unlock value from complex data through advanced analytics, machine learning, and AI-driven decision-making. Their products support a range of commercial use cases, with a strong focus on delivering measurable business outcomes. As they continue to scale, they are investing heavily in their Data & AI capabilities.

The Role

• Lead, mentor, and develop a team of Data Scientists while defining best practices across the function
• Design and deploy machine learning models across forecasting, customer segmentation, and propensity modelling
• Own end-to-end model development including feature engineering, validation, deployment, and monitoring
• Partner with Engineering and Product teams to build scalable, production-ready data science solutions
• Translate analytical outputs into clear commercial recommendations for senior stakeholders
• Drive the adoption of AI tooling and robust model governance across the data science lifecycle

Your Skills & Experience

• Strong commercial experience in Data Science, Machine Learning, or Applied AI
• Experience leading and developing Data Science teams
• Advanced Python and SQL skills
• Expertise in supervised and unsupervised machine learning techniques
• Experience deploying models into production environments using MLOps practices
• Strong communication skills with the ability to influence technical and non-technical stakeholders

What They Offer

• Performance-related bonus
• Private healthcare and additional benefits package
• Opportunity to shape and scale a Data Science function
• Exposure to cutting-edge AI and machine learning projects
• Clear career progression in a high-growth environment

How to Apply
If you’re looking for a Lead Data Scientist opportunity that combines leadership, technical depth, and business impact, please apply today through Harnham.

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