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.
Agentic AI Software Engineer
Houston
$160000 - $180000
+ Data Science & AI
PermanentHouston, Texas
To Apply for this Job Click Here
Senior Agentic AI Engineer (Full Stack)
$160,000-$180,000
4 days/week on-site
Overview
We are seeking a senior software engineer with a strong full-stack background who has evolved into AI engineering and agent development. This role focuses on building, deploying, and optimising intelligent agents and AI-driven workflows that interact with enterprise systems, data sources, and users.
The successful candidate will have hands-on experience developing production-grade AI applications using large language models (LLMs), retrieval-augmented generation (RAG), agent orchestration frameworks, and modern software engineering practices. This position is centred on designing and building AI agents rather than purely traditional application development.
Key Responsibilities
AI Agent Development
- Design and develop AI agents capable of reasoning across complex business processes and interacting with tools, APIs, and enterprise systems.
- Build intelligent support and workflow automation agents that understand intent, retrieve information, and execute tasks.
- Develop agentic workflows combining LLMs, structured data, business logic, external services, and retrieval mechanisms.
- Create memory, context, and personalisation capabilities to improve agent effectiveness.
- Implement guardrails, monitoring, evaluation frameworks, escalation paths, and human oversight mechanisms.
- Measure and improve agent performance across quality, reliability, latency, utilisation, and cost metrics.
Full-Stack Application Development
- Build user-facing applications that enable interaction with AI-powered experiences.
- Develop modern frontend applications using frameworks such as React, Angular, Next.js, or comparable technologies.
- Create backend services, APIs, orchestration layers, and integration services using Python-based frameworks.
- Translate advanced AI capabilities into practical business applications and intuitive user experiences.
- Own solutions end-to-end from architecture through deployment and support.
Data & AI Infrastructure
- Build and maintain data ingestion, integration, and transformation pipelines.
- Develop and support retrieval-augmented generation (RAG) solutions and enterprise search capabilities.
- Design systems supporting context management, retrieval, memory, and personalisation.
- Integrate AI solutions with databases, APIs, analytics platforms, and enterprise applications.
- Ensure data quality, security, reliability, and scalability across AI systems.
LLM Engineering
- Integrate and orchestrate large language models within production environments.
- Design prompting strategies, retrieval approaches, tool-calling frameworks, and multi-step workflows.
- Build AI-powered capabilities including conversational assistants, document intelligence, semantic search, and workflow automation.
- Evaluate models, architectures, and AI platforms for performance, reliability, business fit, and cost efficiency.
- Establish monitoring and evaluation methodologies for production AI solutions.
Engineering Excellence
- Leverage AI-assisted development tools to improve engineering productivity while maintaining high code quality standards.
- Stay current with emerging AI frameworks, tooling, and industry best practices.
- Implement CI/CD, testing, observability, security, and production monitoring practices.
- Support reliable deployment and ongoing optimisation of AI-enabled applications.
Required Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field.
- 8+ years of professional software engineering experience.
- Strong full-stack development experience across frontend and backend technologies.
- Proven experience building and maintaining RESTful APIs and backend services.
- Experience working with data-intensive applications and enterprise integrations.
- Hands-on experience developing AI agents, autonomous workflows, or LLM-powered applications.
- Strong understanding of LLMs, RAG, tool usage, orchestration frameworks, and AI application architectures.
- Experience integrating AI systems with APIs, databases, enterprise platforms, and third-party services.
- Frontend experience with React, Angular, Next.js, or similar frameworks.
- Experience using AI-assisted development tools within software delivery workflows.
- Experience designing agent memory, retrieval, context, evaluation, or reasoning systems.
- Strong understanding of cloud-native application development and deployment.
Preferred Qualifications
- Experience with modern data-platform or lakehouse architectures.
- Experience deploying applications on public cloud platforms.
- Experience with CI/CD pipelines, infrastructure automation, and cloud operations.
- Experience working within agile software delivery environments.
- Experience building highly scalable enterprise applications.
What Success Looks Like
- Demonstrates an AI-first engineering mindset focused on intelligent workflows rather than simple AI integrations.
- Comfortable operating across software engineering, AI, data, and infrastructure domains.
- Balances innovation with reliability, observability, governance, and security.
- Strong product mindset with a focus on measurable business outcomes.
- Effective communicator who collaborates with technical and non-technical stakeholders.
- Thrives in fast-moving environments where requirements and technologies evolve rapidly.
To Apply for this Job Click Here
Lead Data Scientist – Credit Risk
Phoenix
$140000 - $150000
+ Data Science & AI
PermanentPhoenix, Arizona
To Apply for this Job Click Here
Lead Data Scientist
$140,000-$150,000
4 days/week in-office in NW Phoenix
Overview
A leading enterprise organisation is seeking a senior-level Data Scientist to lead the development, validation, and implementation of advanced quantitative models in a highly regulated environment. This role will serve as a technical leader, partnering with business and executive stakeholders to identify financial opportunities, quantify outcomes, and drive data-driven decision making.
The successful candidate will bring deep expertise in risk and financial modelling, strong statistical and mathematical foundations, and the ability to independently deliver complex analytics projects from concept through deployment and governance review.
Key Responsibilities
- Design, develop, validate, and monitor advanced predictive and risk models.
- Analyse large-scale financial, transactional, and customer datasets.
- Apply machine learning and statistical techniques to solve complex business problems.
- Translate model insights into measurable financial impact and business recommendations.
- Lead analytics initiatives from problem definition through implementation and performance tracking.
- Present technical findings and strategic recommendations to senior leadership and executive stakeholders.
- Support model governance activities, regulatory reviews, and external audit processes.
- Collaborate with cross-functional teams to ensure models are aligned with business objectives and compliance requirements.
- Provide technical guidance and mentorship to peers and junior team members.
Required Qualifications
- 8+ years of experience in Data Science, Quantitative Analytics, Risk Analytics, or a related discipline.
- Advanced proficiency in Python and SQL.
- Strong expertise in data modelling, statistical analysis, and quantitative problem solving.
- Experience developing and evaluating gradient boosting and other predictive modelling techniques.
- Proven ability to independently own and drive complex analytical projects.
- Exceptional communication and presentation skills, including experience presenting to executive audiences.
- Demonstrated experience defending models during audits, reviews, or governance assessments.
- Background in financial or risk modelling within a regulated industry.
Required Domain Experience
Candidates should have experience in one or more of the following areas:
- Credit risk modelling
- Financial forecasting and modelling
- Loss estimation and assessment
- Probability of Default (PD) modelling
- Risk scorecard development
- Payment and behavioural modelling
- Credit attribute modelling
- Banking, lending, consumer credit, mortgage, or credit bureau data
- Financial impact analysis
- Risk analytics within regulated financial institutions
Preferred Qualifications
- Bachelor’s degree in a quantitative discipline such as Mathematics, Statistics, Economics, Computer Science, Engineering, or a related field.
- Master’s degree in Data Science, Statistics, Applied Mathematics, Economics, or a similar quantitative discipline preferred.
- Advanced academic training with significant mathematical and statistical coursework.
To Apply for this Job Click Here
Lead Data Scientist – Credit Risk
Alpharetta
$140000 - $150000
+ Data Science & AI
PermanentAlpharetta, Georgia
To Apply for this Job Click Here
Lead Data Scientist
$140,000-$150,000
4 days/week on-site in Alpharetta
Overview
A leading enterprise organisation is seeking a senior-level Data Scientist to lead the development, validation, and implementation of advanced quantitative models in a highly regulated environment. This role will serve as a technical leader, partnering with business and executive stakeholders to identify financial opportunities, quantify outcomes, and drive data-driven decision making.
The successful candidate will bring deep expertise in risk and financial modelling, strong statistical and mathematical foundations, and the ability to independently deliver complex analytics projects from concept through deployment and governance review.
Key Responsibilities
- Design, develop, validate, and monitor advanced predictive and risk models.
- Analyse large-scale financial, transactional, and customer datasets.
- Apply machine learning and statistical techniques to solve complex business problems.
- Translate model insights into measurable financial impact and business recommendations.
- Lead analytics initiatives from problem definition through implementation and performance tracking.
- Present technical findings and strategic recommendations to senior leadership and executive stakeholders.
- Support model governance activities, regulatory reviews, and external audit processes.
- Collaborate with cross-functional teams to ensure models are aligned with business objectives and compliance requirements.
- Provide technical guidance and mentorship to peers and junior team members.
Required Qualifications
- 8+ years of experience in Data Science, Quantitative Analytics, Risk Analytics, or a related discipline.
- Advanced proficiency in Python and SQL.
- Strong expertise in data modelling, statistical analysis, and quantitative problem solving.
- Experience developing and evaluating gradient boosting and other predictive modelling techniques.
- Proven ability to independently own and drive complex analytical projects.
- Exceptional communication and presentation skills, including experience presenting to executive audiences.
- Demonstrated experience defending models during audits, reviews, or governance assessments.
- Background in financial or risk modelling within a regulated industry.
Required Domain Experience
Candidates should have experience in one or more of the following areas:
- Credit risk modelling
- Financial forecasting and modelling
- Loss estimation and assessment
- Probability of Default (PD) modelling
- Risk scorecard development
- Payment and behavioural modelling
- Credit attribute modelling
- Banking, lending, consumer credit, mortgage, or credit bureau data
- Financial impact analysis
- Risk analytics within regulated financial institutions
Preferred Qualifications
- Bachelor’s degree in a quantitative discipline such as Mathematics, Statistics, Economics, Computer Science, Engineering, or a related field.
- Master’s degree in Data Science, Statistics, Applied Mathematics, Economics, or a similar quantitative discipline preferred.
- Advanced academic training with significant mathematical and statistical coursework.
To Apply for this Job Click Here
Staff AI Engineer
Palo Alto
$250000 - $350000
+ Data Science & AI
PermanentPalo Alto, California
To Apply for this Job Click Here
STAFF AI ENGINEER
Palo Alto, California, United States (On-site / Hybrid)
The Role
We’re hiring a Staff AI Engineer to build and scale production-grade GenAI systems powering enterprise AI applications.
This is a high-ownership IC role focused on LLM systems, agent frameworks, and production AI infrastructure. You’ll take foundation models and turn them into scalable, reliable systems used for copilots, automation, and internal workflows.
You’ll work across architecture and implementation in a fast-moving environment with rapid production iteration.
What You’ll Build
- Production LLM-powered services and applications
- Enterprise copilots and conversational AI systems
- Text-to-code and natural language SQL systems
- Agent frameworks and tool-using AI systems
- Workflow automation powered by foundation models
- API layers for LLM integration across systems
- Scalable GenAI infrastructure and deployments
- CI/CD pipelines for AI services
What You Bring
- 8-12+ years software or ML engineering experience
- Strong experience building production LLM or ML systems
- Deep understanding of foundation models and LLM APIs
- Strong backend and distributed systems experience
- Experience with AWS production environments
- Kubernetes / containerized deployment experience
- Strong systems thinking (latency, scaling, reliability trade-offs)
Strong Preference For
- ML engineering background over traditional full-stack
- Experience building GenAI or agentic systems in production
- Strong analytical background (PhD-level NLP/CV a plus)
Why This Role
- Build and scale core GenAI infrastructure with real impact
- High ownership from architecture through production
- Fast iteration cycles and strong technical autonomy
- High visibility with senior technical leadership
- Opportunity to shape foundational AI systems at scale
- Opportunity to shape foundational AI systems at scale
To Apply for this Job Click Here
Data Scientist (Contract)
London
£500 - £550
+ Data Science & AI
ContractLondon
To Apply for this Job Click Here
Contract Data Scientist
Outside IR35
£500 – £550 Per Day
2 Month Duration
2 Days In London Office
The Company
They are a specialist technology business that develops advanced analytics solutions deployed within clients’ secure environments. Their platform helps organisations understand customer behaviour, identify value drivers, and build predictive capabilities using transactional and event data. They work closely with enterprise clients on complex, data-led challenges, combining product innovation with practical delivery.
The Role and Deliverables
- Build customer segmentation, propensity, and forecasting models using large-scale customer datasets.
- Lead clustering and segmentation analysis, with a particular focus on delivering a core segmentation and supporting sub-segmentations.
- Develop models relating to motor and home insurance quote behaviour and customer decision-making.
- Work from defined business requirements and data science briefs to deliver production-ready modelling outputs.
- Package models and supporting assets for handover to deployment and engineering teams.
- Operate as an experienced contractor, delivering value quickly with minimal onboarding.
Your Skills & Experience
- Strong experience building customer segmentation and clustering solutions.
- Proven capability in propensity modelling and predictive analytics.
- Experience developing data science solutions within notebook-based environments.
- Practical experience using Microsoft Fabric and/or Databricks notebooks.
- Ability to build and deploy scalable modelling solutions across large datasets.
- Understanding of insurance customer behaviour, ideally within motor or home insurance.
- Comfortable working independently and delivering outcomes in fast-paced project environments.
How to Apply
If you have strong experience in customer segmentation, propensity modelling, and modern cloud-based data science environments, apply today to discuss this contract opportunity in more detail.
To Apply for this Job Click Here
Contract Data Scientist
London
£500 - £560
+ Data Science & AI
ContractLondon
To Apply for this Job Click Here
The Opportunity
We’re supporting a specialist data and analytics company that develops and licenses a proprietary customer intelligence platform used by enterprise clients. Their platform sits within client environments and leverages first-party customer data, transactions and behavioural events to identify where value is created, forecast future outcomes and drive customer growth through advanced analytics.
They are looking for an experienced Contract Data Scientist to join a critical insurance-focused project and take ownership of model development from day one.
The Project
Working within the insurance sector, you’ll build scalable customer analytics solutions focused on:
- Customer segmentation and clustering
- Propensity modelling
- Forecasting models
- Insurance customer behaviour analysis
- Large-scale model development and delivery
A key deliverable will be the creation of a primary customer segmentation framework, including multiple sub-segmentations, alongside propensity models that support commercial decision-making.
The project specifically focuses on motor and home insurance quote behaviour, so experience understanding insurance products, quote journeys and customer purchasing behaviour is essential.
What You’ll Be Doing
- Developing customer segmentation and clustering models
- Building propensity and predictive models
- Creating forecasting solutions using customer and transactional data
- Working within notebook-based analytics environments
- Packaging models for deployment and handing over to engineering teams
- Collaborating closely with Product, Data Science and Engineering leadership
Essential Skills
- Strong commercial Data Science experience
- Proven background delivering segmentation and clustering projects
- Hands-on propensity modelling experience
- Advanced Python
- Experience working in Databricks and/or Microsoft Fabric
- Experience developing models within notebook environments
- Ability to quickly understand business problems and deliver at pace
- Insurance sector experience
Highly Desirable
- Experience within motor or home insurance
- Understanding of insurance quote journeys and buying behaviour
- Experience delivering customer analytics projects using first-party customer data
- Previous contractor experience in fast-paced delivery environments
To Apply for this Job Click Here
Chief Technology Officer
New York
$300000 - $350000
+ Data Science & AI
PermanentNew York
To Apply for this Job Click Here
Chief Technology Officer (CTO)
Hybrid in New York City
$300,000-350,000 base + Equity
THE COMPANY
Our client is a high-growth AI-native technology company transforming the advertising and marketing ecosystem. The business is building a unified platform designed to replace fragmented agency and martech workflows with intelligent, autonomous systems that streamline campaign strategy, creative development, media activation, optimization, and reporting.
Backed by a strong product vision and an experienced leadership team, the company is at the forefront of applying agentic AI to real-world enterprise workflows. They are now seeking a Chief Technology Officer (CTO) to define the technology strategy, scale the engineering organization, and lead the next phase of growth, specifically around AI agent harness and orchestration infrastructure.
RESPONSIBILITIES
- Define and execute the company’s technology vision, architecture strategy, and long-term product roadmap.
- Own AI agent harnessing and orchestration infrastructure.
- Lead and scale a high-performing engineering organization, fostering a culture of innovation, accountability, and technical excellence.
- Drive the development of AI-native products, agentic workflows, orchestration frameworks, and enterprise-grade automation capabilities.
- Oversee platform architecture, ensuring scalability, reliability, security, observability, and operational excellence as the business grows.
- Partner closely with Product, Commercial, and Customer teams to translate complex advertising and marketing workflows into market-leading software solutions.
- Evaluate emerging AI technologies, LLM frameworks, agent architectures, and infrastructure strategies to maintain a competitive edge.
- Establish engineering best practices covering software development lifecycle, AI governance, deployment standards, testing, and monitoring.
- Build strategic relationships with customers, technology partners, and industry stakeholders to support product innovation and market expansion.
- Lead technical recruitment and organizational growth while mentoring senior engineering talent and future technical leaders.
- Serve as a key member of the executive leadership team, contributing to company-wide strategy, growth planning, and investor discussions.
SKILLS & EXPERIENCE
Required
- Significant software engineering and technology leadership experience, including building and scaling modern SaaS platforms.
- Deep expertise in AI agent harnessing, machine learning, LLM-powered applications, and agentic architectures.
- Strong architectural knowledge across distributed systems, APIs, cloud infrastructure, data platforms, and enterprise integrations.
- Proven track record of delivering complex products from concept through production in fast-moving, high-growth environments.
- Experience building and leading engineering teams, including hiring, mentorship, performance management, and organizational design.
- Demonstrated ability to balance strategic leadership with hands-on technical decision-making.
- Excellent communication skills with the ability to engage technical teams, executive stakeholders, customers, and investors.
Nice to Have
- Experience within advertising technology (AdTech), marketing technology (MarTech), media, or related digital ecosystems.
- Knowledge of enterprise data platforms, CDPs, DSPs, SSPs, advertising APIs, and campaign management systems.
- Exposure to agent orchestration frameworks, multi-agent systems, and model context protocols.
- Experience evaluating or deploying self-hosted and enterprise AI infrastructure.
BENEFITS
- Fully remote-first working environment across the US
- Opportunity to shape technology strategy at an executive level
- Significant influence over product direction and company growth
- Work alongside a highly experienced and senior technical team
- Fast-moving startup environment with substantial ownership and impact
- Equity participation potential and executive-level compensation package
HOW TO APPLY
Please register your interest by sending your CV via the Apply link on this page.
KEY TERMS
CTO | Chief Technology Officer | VP Engineering | AI Leadership | Artificial Intelligence | Agentic AI | Generative AI | LLMs | SaaS | Cloud Architecture | Distributed Systems | Engineering Leadership | AdTech | MarTech | Machine Learning | Platform Engineering | Product Strategy | Remote US | Startup Leadership | Executive Technology Role | AI Agent Harnessing | AI Harness | AI Agent Orchestration
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
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
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
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
Forward Deployed Engineer
New York
$105000 - $250000
+ Data Science & AI
PermanentNew York
To Apply for this Job Click Here
Senior Forward Deployed Engineer (AI & Data Platforms)
New York, NY – Hybrid 3 days a week on site
Up to $220,000 Base Salary + Benefits (dependant on residing state & level of experience)
US Citizen or Green Card holders – visa sponsorship unavailable now or in the future
I’m partnering with a leading consulting organization that is expanding its AI and Data Transformation practice and is seeking a Senior Forward Deployed Engineer to help deliver cutting-edge AI and data solutions within enterprise client environments.
This is a highly client-facing role where you’ll work directly with business and technical stakeholders to build, deploy, and optimize data and AI solutions that drive measurable business outcomes.
What You’ll Be Doing
- Lead end-to-end technical workstreams from discovery through deployment.
- Build and maintain production-grade Python and SQL data pipelines.
- Configure and optimize enterprise data and AI platforms.
- Work closely with engineering, data, and business teams to deliver scalable solutions.
- Drive user adoption through enablement, documentation, and technical leadership.
- Mentor junior team members and contribute to delivery best practices.
What We’re Looking For
- 5+ years of experience in client-facing, consulting, or embedded engineering roles.
- Strong hands-on experience with Python and SQL in production environments.
- Experience building and maintaining modern data pipelines and workflows.
- Background working with enterprise data platforms (Palantir Foundry experience is highly desirable).
- Proven ability to navigate ambiguity and deliver solutions independently.
- Strong communication skills with the ability to partner directly with client stakeholders.
Why Consider This Opportunity?
- Work on innovative AI, GenAI, and data transformation initiatives.
- Join a growing practice focused on solving complex enterprise challenges.
- Exposure to senior business and technology leaders across multiple industries.
- Opportunity to influence the adoption of next-generation AI solutions at scale.
Compensation: Up to $165,000 base salary, plus comprehensive benefits package.
If you’re interested in leveraging AI, data engineering, and client engagement experience to deliver high-impact solutions, I’d love to connect.
#DataEngineering #AI #GenAI #Palantir #Python #SQL #ConsultingJobs #Hiring #RemoteJobs
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