ML DEPLOYMENT
TALENT SOLUTIONS
Our recruitment expertise is specifically tailored for Machine Learning Deployment jobs, recognizing the critical importance of these positions in the successful operationalization of machine learning models. We focus on sourcing professionals who are skilled in navigating the complexities of deploying ML models efficiently and effectively in production environments.
Leveraging our global presence, Harnham has access to a diverse and extensive machine learning and data talent pool, enabling us to find data candidates with the specific skill sets required for Machine learning Deployment jobs. Our local market insights across key regions ensure that we provide candidates who not only meet the technical qualifications but also align with your company’s cultural and operational dynamics.
WHY
HARNHAM?
Our deep-rooted experience in data recruitment positions us as the go-to authority in sourcing talent for ML Deployment roles, ensuring we connect you with candidates capable of transforming your machine learning initiatives into successful, scalable solutions.
We prioritize a deep understanding of your organization’s unique ML Deployment needs, enabling us to deliver precisely matched talent solutions, aligned with your specific technical and strategic requirements.
Harnham’s team of hundreds of recruitment specialists across key global locations brings unparalleled staffing solutions, tailored to the specific needs of your organization, irrespective of the industry.
OUR
SERVICES
- Permanent Recruitment: We identify long-term talent for your ML Deployment team, focusing on professionals who can integrate and grow with your organizational goals.
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- Contract Recruitment: Our contract recruitment services provide the agility to meet your immediate ML Deployment needs with highly skilled temporary professionals.
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- Customized Talent Consulting: We offer bespoke talent consulting services, including talent mapping, market analysis, and strategic workforce planning, to optimize your recruitment strategy and build a robust ML Deployment team.
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Contact us today to discover how our specialized services can help you build a high-performing ML Deployment team and drive your organization's success in the machine learning domain.
JOBS
LATEST mL deployment
JOBS
Harnham are a specialist Data & AI recruitment business with teams that only focus on niche areas.
Staff Finance Data Scientist – Consumption Forecasting
San Francisco
$240000 - $300000
+ Data Science & AI
PermanentSan Francisco, California
To Apply for this Job Click Here
Staff Data Scientist, Finance – Consumption Forecasting
Location: San Francisco or New York | Hybrid (3 days per week in office)
Salary: $240-300k base + bonus + equity (RSUs)
This is a rare chance to own forecasting infrastructure at the center of a high-growth, consumption-based developer platform, one that powers some of the world’s most dynamic applications and scales with every developer and enterprise building on it.
As a consumption-based business, forecasting usage across compute, bandwidth, edge, and storage isn’t a support function. It’s foundational to how we plan infrastructure, revenue, and long-term strategy. This role exists to lead that work at the highest level.
What you’ll own
This is a senior individual contributor role with organization-wide impact. You’ll define forecasting methodology, build systems that scale with a rapidly growing platform, and sit at the intersection of Finance, Infrastructure, Product, and GTM with direct visibility to executive leadership.
- Own production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration from first principles to live system
- Build forecasting systems that account for usage-based pricing dynamics, consumption patterns, and customer lifecycle across the platform, built for how this business actually works, not retrofitted SaaS models
- Design hierarchical forecasting models across account, cohort, segment, and global aggregate levels, covering operational, quarterly, and long-range planning cycles
- Establish backtesting, monitoring, and explainability standards that make forecast accuracy transparent and defensible
- Build scenario simulation frameworks to evaluate pricing changes, packaging adjustments, and product launches
- Partner with Finance on board-level reporting, with Infrastructure Engineering on capacity planning, and with Product and GTM on adoption curves and usage drivers
- Set forecasting best practices across the broader Data organization
What we’re looking for
- 7+ years in data science, quantitative analytics, or applied statistics at senior or staff level
- Deep expertise in time-series forecasting and statistical modelling in a usage-based or SaaS environment
- Proven track record building and productionizing ML systems at scale
- Strong Python and SQL, with experience on large-scale usage and billing datasets
- Familiarity with probabilistic modelling, hierarchical forecasting, and causal inference
- Experience partnering with Finance or executive leadership on planning cycles
- Comfortable operating autonomously in fast-moving, ambiguous environments
Nice to have
- Background in cloud infrastructure, developer tools, or consumption-based revenue models
- Familiarity with modern data stacks: Snowflake, Delta Lake, dbt, Airflow
- Prior technical mentorship or informal leadership experience
To Apply for this Job Click Here
Senior Data Scientist – Pricing
London
£60000 - £75000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Senior Data Scientist – Pricing
London / Leicester | £60,000 – £75,000
This is an exciting opportunity for a Senior Data Scientist to join a highly advanced analytics function focused on pricing innovation. You’ll work on developing cutting-edge machine learning models, leveraging new technologies and data sources to influence commercial strategy and deliver tangible business impact.
The Company
They are a data-driven organisation that has invested heavily in its analytics and pricing capabilities. Their Data Science team sits at the heart of strategic decision-making, helping to improve risk assessment, customer outcomes, and commercial performance. Working within a collaborative environment, you’ll partner with experts across analytics, engineering, and business functions to drive innovation and challenge conventional approaches.
The Role
You will:
- Develop and deploy machine learning models that support pricing and risk management strategies.
- Build predictive models focused on claims outcomes, fraud detection, and key business performance metrics.
- Create and maintain analytical tools used to manage and optimise risk portfolios.
- Identify, assess, and utilise new data sources to improve model performance and business outcomes.
- Engineer new predictive features that can be incorporated into pricing algorithms.
- Take ownership of projects across the full machine learning lifecycle, from exploratory analysis through to deployment and monitoring.
- Collaborate with Data Scientists, Data Engineers, Analysts, and business stakeholders to deliver commercial value.
- Explore emerging machine learning techniques and assess their practical application within the business.
Your Skills & Experience
- Strong commercial experience delivering end-to-end machine learning projects.
- Excellent Python and SQL skills.
- Experience with Azure Machine Learning, Azure Cloud Services, and Git.
- Strong understanding of model deployment, monitoring, evaluation, and optimisation.
- Ability to translate complex business problems into scalable analytical solutions.
- Experience engaging with a range of stakeholders to define requirements and drive successful outcomes.
- Strong communication skills and a collaborative approach to problem-solving.
- Passion for applying advanced analytics and machine learning to real-world business challenges.
How to Apply
To find out more about this opportunity, please apply with your CV and we’ll be in touch to discuss the role in more detail.
To Apply for this Job Click Here
Data Scientist
Liverpool
£50000 - £55000
+ Data Science & AI
PermanentLiverpool, Merseyside
To Apply for this Job Click Here
Data Scientist
Liverpool (Hybrid) | Up to £55,000
Looking to apply advanced analytics and machine learning in a role where your work directly influences business decisions? This is an opportunity to join a well-established consumer-focused organisation investing heavily in its data capabilities. You’ll work on a broad range of projects, turning complex datasets into actionable insights and delivering measurable commercial impact.
The Company
They are a recognised organisation with a large customer base and a growing commitment to data-driven decision making. Their analytics and technology teams play a key role in shaping strategy, improving customer outcomes, and driving operational performance. With continued investment in AI, machine learning, and cloud technologies, they offer an environment where innovation and collaboration are actively encouraged.
The Role
You will be responsible for:
- Collecting, cleaning, and preparing data from multiple sources to ensure quality and accuracy.
- Applying statistical analysis and machine learning techniques to solve business challenges.
- Building, deploying, and maintaining predictive models that deliver tangible value.
- Developing and enhancing AI and machine learning solutions using modern cloud-based tools.
- Creating dashboards and visualisations that communicate insights clearly to stakeholders.
- Working closely with analysts, engineers, and business teams to deliver data science projects.
- Identifying trends, opportunities, and risks through advanced analytics.
- Keeping up to date with the latest developments in data science, AI, and machine learning.
Your Skills & Experience
- Strong commercial experience delivering data science solutions.
- Excellent Python or R programming skills.
- Strong SQL capabilities for data extraction and analysis.
- Experience with forecasting, statistical modelling, and machine learning techniques.
- Knowledge of the full data science lifecycle from model development through to deployment and monitoring.
- Experience working with cloud platforms such as Azure, AWS, or GCP.
- Ability to communicate technical findings to both technical and non-technical stakeholders.
- Passion for using data to solve real-world business problems.
How to Apply
To find out more about this opportunity, please apply with your CV and we’ll be in touch to discuss the role in more detail.
To Apply for this Job Click Here
MLOps Platform Engineer
Phoenix
$65 - $77
+ Data Science & AI
ContractPhoenix, Arizona
To Apply for this Job Click Here
MLOps Platform Engineer
Phoenix, Arizona
This is a unique opportunity to build an enterprise-scale MLOps platform from the ground up. Joining a greenfield initiative, you will play a pivotal role in designing and operationalizing the infrastructure, automation, and governance required to deploy, monitor, and scale machine learning models in production. This project offers the chance to shape long-term MLOps strategy while working closely with Data Science and Data Engineering teams to establish best practices across the organization.
The Company
They are a large, established organization undergoing significant investment in data, analytics, and machine learning capabilities. With a strong focus on innovation and operational excellence, they are building modern data and AI platforms to support critical business initiatives. Their teams are committed to creating scalable, governed, and sustainable solutions that enable advanced analytics and machine learning at enterprise scale.
The Role and Deliverables
- Design and build a production-grade MLOps platform using Snowflake and related machine learning capabilities.
- Develop reusable ML pipelines covering training, validation, deployment, inference, monitoring, and lifecycle management.
- Establish model governance standards including versioning, approval workflows, lineage tracking, rollback procedures, and auditability.
- Implement model observability frameworks for performance monitoring, drift detection, data quality validation, and service reliability.
- Build and automate CI/CD processes for machine learning workflows, including testing, release management, and deployment controls.
- Partner closely with Data Scientists and Data Engineers to productionize models and ensure reliable integration with enterprise data platforms.
Your Skills & Experience
- Strong experience building MLOps platforms or machine learning infrastructure in production environments.
- Proven capability designing and implementing model deployment, monitoring, tracking, versioning, and registry processes.
- Advanced Python and SQL skills with experience developing and maintaining machine learning pipelines.
- Experience building CI/CD pipelines and automation frameworks for machine learning systems.
- Hands-on experience with enterprise machine learning platforms such as Snowflake ML, Databricks, AWS SageMaker, or similar technologies.
- Strong understanding of the relationship between data engineering pipelines and downstream machine learning workflows.
- Experience working with cloud platforms, ideally AWS.
- Ability to collaborate effectively with Data Scientists and Data Engineers to define requirements and deliver scalable solutions.
- Familiarity with Snowpark, Feature Stores, Model Registry capabilities, or other modern MLOps tooling is advantageous.
- Experience with medallion architectures, ML observability, AI agents, containers, dbt, Splunk, or near real-time machine learning environments would be beneficial.
How to Apply
If you are an experienced MLOps Platform Engineer who enjoys building scalable machine learning platforms from scratch and driving best practices across enterprise AI environments, please apply today.
To Apply for this Job Click Here
Data Scientist
Liverpool
£45000 - £55000
+ Data Science & AI
PermanentLiverpool, Merseyside
To Apply for this Job Click Here
Data Scientist
£45,000 – £55,000
Merseyside (3 days a week in office)
This is an excellent opportunity to join a growing Data Science function at a business investing heavily in its data and AI capabilities. You’ll work on high-impact customer and commercial projects, helping to shape how machine learning is adopted across the organisation while gaining exposure to cutting-edge tools and a rapidly evolving data environment.
THE COMPANY
This organisation is investing heavily in its Data and AI capabilities, with a focus on building a scalable Data Science function that delivers real business impact. As Data Science becomes increasingly central to decision-making, you’ll have the opportunity to work on high-profile customer and commercial projects with strong backing from senior leadership. They foster a collaborative, pragmatic culture where Data Scientists are encouraged to move beyond experimentation and deliver solutions that create measurable value. The focus is on deploying models into production and embedding data-driven thinking across the business.
THE ROLE
As a Data Scientist, you will work closely with senior stakeholders, analysts, engineers, and fellow Data Scientists to deliver machine learning solutions across a range of customer and commercial use cases.
Specifically, you can expect to be involved in the following:
- Building and deploying predictive machine learning models
- Developing customer segmentation and customer lifetime value models
- Creating forecasting solutions to support business planning
- Delivering propensity and churn models to improve customer engagement
- Translating complex analytical findings into clear business recommendations
- Collaborating with engineering teams to support model deployment and operationalisation
- Supporting the development of a modern Data Science platform
- Working with cloud-based machine learning tools and technologies
- Engaging directly with stakeholders to understand challenges and define analytical solutions
SKILLS AND EXPERIENCE
The successful Data Scientist will have the following skills and experience:
- Strong commercial experience in Data Science and machine learning
- Advanced Python and SQL skills
- Experience using statistical modelling and predictive analytics techniques
- Knowledge of machine learning algorithms such as XGBoost and related ensemble methods
- Experience delivering projects across the full Data Science lifecycle, from problem definition through to deployment
- Ability to communicate technical concepts clearly to non-technical audiences
- Experience working with customer analytics, segmentation, churn, propensity modelling, forecasting, or related use cases
- Exposure to cloud environments such as Azure or GCP is beneficial
- Experience with Azure ML, Vertex AI, or similar machine learning platforms is advantageous
BENEFITS
The successful Data Scientist will receive the following benefits:
- Salary between £45,000 – £55,000 – depending on experience
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
To Apply for this Job Click Here
Data Scientist
Liverpool
£45000 - £55000
+ Data Science & AI
PermanentMerseyside
To Apply for this Job Click Here
Data Scientist
£45,000 – £55,000
Merseyside (3 days a week in office)
This is an excellent opportunity to join a growing Data Science function at a business investing heavily in its data and AI capabilities. You’ll work on high-impact customer and commercial projects, helping to shape how machine learning is adopted across the organisation while gaining exposure to cutting-edge tools and a rapidly evolving data environment.
THE COMPANY
This organisation is investing heavily in its Data and AI capabilities, with a focus on building a scalable Data Science function that delivers real business impact. As Data Science becomes increasingly central to decision-making, you’ll have the opportunity to work on high-profile customer and commercial projects with strong backing from senior leadership. They foster a collaborative, pragmatic culture where Data Scientists are encouraged to move beyond experimentation and deliver solutions that create measurable value. The focus is on deploying models into production and embedding data-driven thinking across the business.
THE ROLE
As a Data Scientist, you will work closely with senior stakeholders, analysts, engineers, and fellow Data Scientists to deliver machine learning solutions across a range of customer and commercial use cases.
Specifically, you can expect to be involved in the following:
- Building and deploying predictive machine learning models
- Developing customer segmentation and customer lifetime value models
- Creating forecasting solutions to support business planning
- Delivering propensity and churn models to improve customer engagement
- Translating complex analytical findings into clear business recommendations
- Collaborating with engineering teams to support model deployment and operationalisation
- Supporting the development of a modern Data Science platform
- Working with cloud-based machine learning tools and technologies
- Engaging directly with stakeholders to understand challenges and define analytical solutions
SKILLS AND EXPERIENCE
The successful Data Scientist will have the following skills and experience:
- Strong commercial experience in Data Science and machine learning
- Advanced Python and SQL skills
- Experience using statistical modelling and predictive analytics techniques
- Knowledge of machine learning algorithms such as XGBoost and related ensemble methods
- Experience delivering projects across the full Data Science lifecycle, from problem definition through to deployment
- Ability to communicate technical concepts clearly to non-technical audiences
- Experience working with customer analytics, segmentation, churn, propensity modelling, forecasting, or related use cases
- Exposure to cloud environments such as Azure or GCP is beneficial
- Experience with Azure ML, Vertex AI, or similar machine learning platforms is advantageous
BENEFITS
The successful Data Scientist will receive the following benefits:
- Salary between £45,000 – £55,000 – depending on experience
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
To Apply for this Job Click Here
Lead AI Engineer
London
£95000 - £115000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Lead AI Engineer
£95,000 – £115,000
King’s Cross, London (1-2 days a week in office)
This is an opportunity to lead the design, architecture, and delivery of production-grade AI systems that create measurable business impact. You will work on high-value initiatives, building scalable AI solutions that are embedded directly into core business processes rather than standalone prototypes.
THE COMPANY
They are a well-established organisation investing heavily in AI innovation to transform business operations and deliver long-term value. Their focus is on deploying practical, scalable AI solutions that support real workflows and business outcomes. You will join a technology-driven environment where engineering excellence, collaboration, and innovation are highly valued.
THE ROLE
As a Lead AI Engineer, you will
Specifically, you can expect to be involved in the following:
- Own the technical direction, architecture, and implementation of AI systems end-to-end.
- Design and build LLM-powered and agent-based solutions from concept through to production.
- Establish engineering standards, reusable patterns, and scalable frameworks across AI initiatives.
- Make key decisions on models, tooling, infrastructure, and system design.
- Ensure AI systems are robust, observable, secure, and production-ready through effective evaluation, monitoring, and guardrails.
- Provide technical leadership and guidance to engineers working on AI projects.
SKILLS AND EXPERIENCE
The successful Lead AI Engineer will have the following skills and experience:
- Strong commercial experience delivering production-grade AI systems from design through deployment.
- Deep expertise in Generative AI, Large Language Models (LLMs), orchestration, prompting, and evaluation.
- Experience building agentic or multi-step AI systems.
- Excellent software engineering fundamentals across APIs, system design, and cloud-based architecture.
- Ability to define technical direction and operate effectively in complex or evolving environments.
- Experience influencing engineering standards and best practices across multiple projects.
- Exposure to AI platforms, reusable frameworks, LLMOps/MLOps, or enterprise AI environments would be beneficial.
BENEFITS
The successful Lead AI Engineer will receive the following benefits:
- Salary between £95,000 – £115,000 – depending on experience
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
To Apply for this Job Click Here
Senior ML Ops Engineer
London
£75000 - £85000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Senior MLOps Engineer
£75,000 – £85,000
London (1-2 days a week in office)
This is an opportunity to join a growing AI and data-driven organisation where your work will have a direct impact on the development and delivery of advanced machine learning solutions. You will play a key role in shaping scalable MLOps infrastructure, enabling AI products to operate reliably across a diverse client base while contributing to meaningful, real-world outcomes.
THE COMPANY
They are a mission-led technology business that uses data, machine learning, and advanced analytics to help organisations make better decisions. Their platform combines data engineering, AI, and predictive modelling to generate actionable insights at scale. As they continue to grow, they are investing heavily in their AI capabilities and platform infrastructure, creating an exciting environment for engineers who enjoy solving complex technical challenges.
THE ROLE
As a Senior MLOps Engineer, you will join the platform engineering function, owning and evolving the infrastructure that underpins the organisation’s AI services
Specifically, you can expect to be involved in the following:
- Designing and maintaining scalable MLOps infrastructure that supports machine learning, NLP, knowledge representation, and AI applications.
- Deploying and managing machine learning models using Azure ML, Azure Kubernetes Service (AKS), and associated cloud technologies.
- Building and maintaining production-grade orchestration pipelines for model training, inference, monitoring, and retraining.
- Developing CI/CD pipelines to automate testing, deployment, and operational processes.
- Implementing observability, monitoring, and alerting frameworks to ensure platform reliability and performance.
- Driving best practice around Responsible AI, governance, transparency, and auditability.
- Collaborating with engineering, delivery, and consulting teams to support the adoption and scaling of AI solutions
- Other key responsibilities & selling points of role.
SKILLS AND EXPERIENCE
The successful Senior MLOps Engineer will have the following skills and experience:
- Strong commercial experience in MLOps, platform engineering, infrastructure engineering, or a related field.
- Advanced Python development skills within production environments.
- Expertise with Azure-native MLOps tools, including model endpoints, pipelines, registries, environments, and compute resources.
- Experience deploying and supporting containerised workloads on Kubernetes.
- Strong knowledge of CI/CD practices using Azure DevOps or similar tooling.
- Experience with infrastructure-as-code technologies such as Terraform, Bicep, or Pulumi.
- Knowledge of monitoring and observability tooling such as Prometheus and Grafana.
- Experience with orchestration platforms including Dagster, Airflow, Prefect, or similar.
BENEFITS
The successful Senior MLOps Engineer will receive the following benefits:
- Salary between £75,000 – £85,000 – depending on experience
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
To Apply for this Job Click Here
Senior MLOps Engineer 201043
City of London
£75000 - £85000
+ Data Science & AI
PermanentCity of London, London
To Apply for this Job Click Here
Senior MLOps Engineer
London (Hybrid) | Salary: up to £85,000
This is an opportunity to join a growing AI and data organisation where your work will directly support the deployment, scalability, and reliability of innovative machine learning solutions. You will play a pivotal role in building the infrastructure that enables advanced AI services to deliver real-world impact at scale.
The Company
They are a mission-led technology organisation that uses data, machine learning, and AI to help organisations make better decisions and deliver meaningful outcomes. With a growing client base and continued investment in their platform, they are expanding their engineering capabilities to support the next stage of growth. Their environment combines technical excellence with a strong focus on responsible AI, innovation, and continuous improvement. You will be joining a collaborative team where your expertise will help shape both the platform and the wider AI strategy.
The Role
- Build, maintain, and evolve the cloud infrastructure that supports machine learning and AI services in production.
- Deploy, manage, and monitor machine learning models using Azure ML, Azure Kubernetes Service (AKS), and related Azure services.
- Design and develop robust orchestration pipelines for model training, deployment, inference, and retraining workflows.
- Implement infrastructure-as-code solutions using tools such as Terraform, Bicep, or similar technologies.
- Establish monitoring, logging, alerting, and observability frameworks to ensure reliability and performance.
- Support scalable deployment across multiple client environments while maintaining security and operational excellence.
- Collaborate with data scientists, engineers, and wider business stakeholders to enable successful AI delivery.
- Contribute to AI governance, best practices, and responsible AI principles across the organisation.
Your Skills & Experience
- Strong commercial experience within MLOps, Platform Engineering, or Infrastructure Engineering supporting machine learning systems.
- Advanced Python programming skills with a strong software engineering mindset.
- Hands-on experience with Azure-native MLOps services, including model deployment, pipelines, environments, and compute resources.
- Proven expertise deploying and managing containerised applications on Kubernetes.
- Experience building and maintaining CI/CD pipelines using Azure DevOps or similar tools.
- Knowledge of infrastructure-as-code approaches using Terraform, Bicep, Pulumi, or equivalent technologies.
- Experience implementing monitoring and observability solutions using tools such as Prometheus, Grafana, or similar.
- Familiarity with orchestration platforms including Dagster, Airflow, Prefect, or related technologies.
Desirable experience includes:
- Model serving infrastructure for real-time or batch inference workloads.
- Multi-tenant platform environments.
- Vector databases such as Qdrant.
- Development of high-performance APIs and data-intensive services.
- Broader Azure ecosystem expertise including Azure Container Registry, Azure Blob Storage, Azure Monitor, and Azure Key Vault.
What They Offer
- The opportunity to work on innovative AI and machine learning projects with genuine societal impact.
How to Apply
If you are an experienced Senior MLOps Engineer looking to build scalable AI infrastructure in a collaborative and purpose-driven environment, apply today to discuss the opportunity in more detail.
To Apply for this Job Click Here
Data Scientist
Liverpool
£50000 - £55000
+ Data Science & AI
PermanentLiverpool, Merseyside
To Apply for this Job Click Here
Data Scientist
Merseyside (3 days per week) | Up to £55,000
Looking to make a tangible impact with Data Science in a business that is investing heavily in data and AI? This is an opportunity to join a growing team at a pivotal stage in its transformation, helping to build scalable machine learning solutions that drive real commercial outcomes. You’ll work closely with senior stakeholders and play a key role in shaping how Data Science is embedded across the organisation.
The Company
They are a well-established consumer-focused organisation undergoing a significant data and AI transformation. With strong investment in technology, analytics, and customer insight capabilities, they are building a modern Data Science function focused on delivering measurable business value.
The team is moving beyond ad hoc analytics towards scalable, production-ready machine learning solutions. Data is at the heart of strategic decision-making, creating an exciting environment for a commercially minded Data Scientist to make an impact.
The Role
As a Data Scientist, you will work closely with Data Science leadership, engineers, analysts, and business stakeholders to develop and deploy machine learning solutions across a range of customer and commercial use cases.
Responsibilities include:
- Building, validating, and deploying predictive and machine learning models
- Developing customer segmentation and customer lifetime value models
- Supporting forecasting initiatives to improve commercial planning
- Delivering targeted customer and personalisation use cases
- Working across the full Data Science lifecycle from problem definition through to production deployment
- Collaborating with technical and non-technical stakeholders to translate business challenges into analytical solutions
- Contributing to the development of a scalable Data Science platform and best practice framework
- Presenting insights and recommendations clearly to business audiences
Your Skills & Experience
- Strong commercial experience in Data Science and machine learning
- Excellent Python skills, with SQL expertise
- Experience delivering end-to-end Data Science projects from development to deployment
- Knowledge of statistical modelling, forecasting, and predictive analytics techniques
- Experience communicating technical concepts to non-technical stakeholders
- Ability to work in a collaborative, business-focused environment
- Exposure to cloud technologies such as GCP or Azure is advantageous
- Experience with Vertex AI, Azure ML, or similar machine learning platforms is beneficial
What They Offer
- Salary up to £55,000
- Hybrid working with 3 days per week in Knowsley
- Opportunity to join a growing Data Science team at an early stage of its journey
- Exposure to high-profile customer and commercial projects
- Significant opportunity to influence tooling, processes, and best practice
- Ongoing professional development and career progression opportunities
- Inclusive and collaborative working environment
How to Apply
- If you’re a Data Scientist who enjoys solving real business problems with data and wants to help shape a growing machine learning capability, apply today to find out more.
To Apply for this Job Click Here
Lead Data Scientist
Atlanta
$140000 - $150000
+ Data Science & AI
PermanentAtlanta, Georgia
To Apply for this Job Click Here
Lead Data Scientist
Base salary: $140,000 – $150,000
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.
Work Model / Location / Engagement Details
- Hybrid work arrangement requiring onsite attendance four days per week (Monday through Thursday).
To Apply for this Job Click Here
Lead Data Scientist
Dallas
$140000 - $150000
+ Data Science & AI
PermanentDallas, Texas
To Apply for this Job Click Here
Lead Data Scientist
Base salary: $140,000 – $150,000
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.
Work Model / Location / Engagement Details
- Hybrid work arrangement requiring onsite attendance four days per week (Monday through Thursday).
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