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ML Scientist

$250,000-$280,000

Overview

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

Key Responsibilities

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

Required Qualifications

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

Preferred Qualifications

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

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AI Engineer
London (Hybrid – 3x a week)

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

The Role

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

Your Skills & Experience

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

What They Offer

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

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

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Chief Scientist

$300,000- $350,000

Overview

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

Key Responsibilities

Scientific Leadership & Strategy

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

Research Organisation Leadership

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

Executive Leadership

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

Financial Management

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

External Engagement

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

Culture & Ethical Leadership

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

Required Qualifications

Education

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

Experience

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

Technical Expertise

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

Leadership Skills

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

Preferred Qualifications

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

Work Model / Reporting Structure

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

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Senior Machine Learning Scientist

London (Remote)

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

The Role

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

Your Skills & Experience

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

What They Offer

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

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

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Senior Manager, Full-Stack Engineering

$190,000-$210,000

4 days/week on-site in Houston or Austin

Overview

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

Key Responsibilities

Technical Leadership & Delivery

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

Team Management

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

Engineering Standards & Quality

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

Cross-Functional Collaboration

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

Required Qualifications

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

Preferred Qualifications

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

Work Model / Location / Engagement Details

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

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Senior Machine Learning Engineer

$140,000-$190,000

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

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

Required Qualifications

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

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

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

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

The Role

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

Your Skills & Experience

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

What They Offer

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

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

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

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

The Role
As a Senior Data Analyst, you will:

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

Your Skills & Experience

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

What They Offer

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

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

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Product Analyst
Up to £85,000 + Bonus
Hybrid – London (2x days per week)

This is an exciting opportunity to join a fast‑growing digital organisation where data sits at the heart of every decision. You will play a pivotal role in shaping how product teams understand user behaviour, influence product strategy, and unlock opportunities that drive measurable impact.

The Company
They are a consumer-focused digital business committed to creating meaningful experiences for their members. With a mission-driven culture and a period of rapid expansion, they are investing heavily in data, analytics, and experimentation. Collaboration, innovation, and continuous learning are central to how they operate. They offer a flexible hybrid environment with a strong focus on development and wellbeing.

The Role
* Use quantitative analysis and data storytelling to uncover user behaviours and inform product strategy.
* Generate hypotheses, support experiments, and identify new opportunities.
* Define and maintain key product metrics, ensuring clarity and alignment across teams.
* Build dashboards and self-serve tools that empower stakeholders.
* Conduct deep-dive analyses to influence strategic decisions.
* Contribute to shared knowledge and promote best practices across data teams.

Your Skills and Experience
* Strong commercial experience in analytical roles within digital products.
* Proficient in SQL and analytical tools such as Python or R.
* Skilled in dashboarding with tools like Looker, Tableau, or similar.
* Confident translating complex data into actionable insight for varied audiences.
* Curious, collaborative, and proactive in solving problems.

What They Offer
Competitive salary, hybrid working, comprehensive benefits, generous leave, wellbeing support, and a culture that champions growth.

How to Apply
To register your interest, send your CV or apply below.

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Senior Data Scientist

Hybrid – Leicester (1x day a week)

£75,000 – £85,000 + bonus

Looking to apply advanced machine learning in a highly commercial environment? This is an opportunity to join a data-driven organisation where analytics sits at the heart of strategic decision-making. You’ll work on innovative pricing and risk modelling challenges, helping shape how data and machine learning drive business performance.

The Company

They are a well-established consumer-focused organisation with a strong investment in data, analytics, and technology. Their data science function plays a critical role in driving commercial outcomes through advanced modelling and predictive analytics. With a collaborative culture and modern cloud-based technology stack, they offer an environment where innovation and experimentation are encouraged. You will work alongside talented data scientists, analysts, and engineers to deliver impactful solutions at scale.

The Role

As a Senior Data Scientist, you will develop advanced machine learning solutions that support pricing, risk assessment, and business performance.

Responsibilities include:

• Building and deploying predictive machine learning models across a range of commercial use cases
• Developing analytical tools to improve risk portfolio management and decision-making
• Creating innovative features and data assets to enhance model performance
• Identifying and evaluating new data sources that can drive commercial value
• Taking models through the full lifecycle from exploration and development to deployment, monitoring, and optimisation
• Partnering with stakeholders to define business problems and deliver effective solutions
• Working closely with Data Engineers, Data Scientists, Analysts, and other technical specialists
• Contributing to the adoption of emerging machine learning techniques and best practices

Your Skills & Experience

• Strong commercial experience delivering machine learning projects from discovery through to deployment and ongoing model management
• Expertise in Python and SQL
• Experience working with Azure Machine Learning and wider Azure cloud technologies
• Knowledge of version control tools such as Git
• Ability to translate complex business challenges into analytical solutions
• Strong stakeholder management and communication skills
• Experience working in cross-functional data and analytics environments
• Passion for innovation and applying new machine learning approaches to real-world challenges

What They Offer

• Competitive salary
• Annual bonus scheme
• Car allowance
• Private medical insurance
• Matched pension contributions
• Life assurance and income protection
• Hybrid and flexible working arrangements
• Generous annual leave allowance
• Health, wellbeing, and financial support benefits
• Ongoing learning, development, and career progression opportunities within a growing data science function

How to Apply

If you’re interested in this Senior Data Scientist opportunity, apply today to discuss how your experience aligns with the role.

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Location: Concord, CA (Hybrid)

Schedule: Approximately 3 days onsite per week

About the Company

We are a mission-driven financial services organization dedicated to helping individuals and families achieve long-term financial well-being. With a strong reputation for member service, innovation, and operational excellence, we leverage data and technology to make smarter business decisions, deliver exceptional customer experiences, and drive sustainable growth.

As the organization continues to invest in digital transformation, analytics has become a key strategic function supporting executive leadership, marketing, product development, operations, and long-term business planning.

About the Role

We are seeking a Senior Marketing Analyst to join a growing Business Intelligence & Analytics team. This individual will serve as a strategic partner to Marketing and senior leadership, transforming complex data into actionable insights that drive customer acquisition, product adoption, digital engagement, and overall business growth.

This is not a reporting-only role. We’re looking for someone who can go beyond dashboards and metrics to identify opportunities, answer critical business questions, and provide data-driven recommendations that influence decision-making.

The ideal candidate combines strong technical skills in SQL and business intelligence tools with expertise in marketing analytics, digital analytics, experimentation, and statistical analysis.

This role will play a key part in a major website initiative, helping shape measurement strategies, design tracking frameworks, and establish reporting that supports ongoing optimization efforts.

What You’ll Do

• Analyze marketing campaign performance and provide actionable recommendations to improve results
• Develop and automate reporting solutions, dashboards, and executive-level presentations
• Design and implement measurement frameworks for digital marketing and web analytics initiatives
• Partner with marketing stakeholders to evaluate acquisition, engagement, conversion, and retention performance
• Lead web analytics efforts related to website optimization and digital experience measurement
• Create and maintain Power BI dashboards and reporting solutions
• Perform attribution analysis and evaluate channel performance across digital marketing programs
• Design and analyze A/B tests and other experimentation programs
• Develop forecasting models and predictive analyses to support business and marketing initiatives
• Conduct customer, segmentation, churn, and lifetime value analyses
• Identify opportunities to automate reporting and improve analytical processes
• Present findings and recommendations to technical and non-technical stakeholders, including executive leadership
• Ensure data accuracy, integrity, and consistency across reporting environments

Must-Have Qualifications

• 5+ years of experience in analytics, marketing analytics, business analytics, or a related field
• Advanced SQL skills with the ability to write complex queries, build views, and develop analytical datasets
• Experience building dashboards and reports in Power BI (Tableau experience also considered)
• Strong background in marketing analytics and campaign performance measurement
• Experience with Google Analytics (GA4) or Adobe Analytics
• Knowledge of attribution methodologies and digital marketing measurement
• Experience analyzing paid media performance, customer acquisition metrics, and marketing ROI
• Strong understanding of statistics and quantitative analysis
• Hands-on experience designing and evaluating A/B tests or other experimentation frameworks
• Ability to translate complex findings into business recommendations
• Excellent communication and stakeholder management skills
• Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Information Systems, Finance, or a related discipline

Nice-to-Have Qualifications

• Experience working within banking, credit unions, fintech, or financial services
• Knowledge of Azure cloud technologies and modern data environments
• Experience with forecasting, predictive modeling, churn analysis, or customer lifetime value modeling
• Experience supporting website redesigns, digital transformation initiatives, or tracking strategy implementations
• Familiarity with data warehousing concepts and modern analytics infrastructure
• Experience presenting analytical findings to executive leadership teams
• Exposure to startup or fast-paced, high-growth environments

What Success Looks Like

In this role, you’ll be successful if you:

• Identify opportunities that improve marketing performance and business outcomes
• Deliver insights that influence strategic decision-making
• Build scalable reporting solutions that reduce manual work
• Confidently recommend solutions rather than simply reporting metrics
• Effectively partner with marketing, operations, product, and executive stakeholders
• Balance multiple priorities while maintaining a high level of accuracy and quality

Compensation & Benefits

Base Salary: $131,000 – $164,000

Additional Benefits Include:

• Annual bonus opportunity
• Comprehensive medical, dental, and vision coverage
• 401(k) with employer contributions and immediate vesting
• Generous paid time off and sick leave programs
• Tuition reimbursement
• Student loan repayment assistance
• Life insurance and disability coverage
• Professional development opportunities

Work Environment

• Hybrid work model with approximately three days onsite per week
• Collaborative, highly visible position with exposure to executive leadership
• Opportunity to work on strategic, business-critical initiatives
• High-growth analytics function with significant influence across the organization

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Are you an architect who thrives on transforming complex data ecosystems into modern, intelligent platforms? We are partnering with a highly respected enterprise organization seeking a visionary AWS Data Architect to lead the evolution of its next-generation cloud data strategy.

This is a high-impact opportunity for an experienced architect who enjoys operating at both the strategic and technical levels, influencing enterprise-wide decisions, designing scalable cloud-native solutions, and leveraging emerging AI capabilities to create measurable business value.

You will play a pivotal role in defining the future-state architecture of a rapidly evolving data environment, driving modernization initiatives, and introducing innovative approaches that enable faster decision-making, improved customer experiences, and accelerated delivery across the organization.

Why This Opportunity Stands Out

• Own the vision and roadmap for a large-scale AWS data ecosystem.
• Influence executive-level technology strategy and architectural direction.
• Drive cloud-native modernization initiatives from concept through execution.
• Work with cutting-edge technologies including Agentic AI, Vector Databases, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP).
• Build scalable, event-driven architectures utilizing real-time and streaming technologies.
• Establish enterprise architecture patterns that accelerate engineering productivity and innovation.
• Lead and mentor high-performing technical teams while shaping best practices across the organization.

What You’ll Be Doing

As the AWS Data Architect, you will serve as a trusted advisor and strategic leader responsible for designing and guiding the organization’s data transformation journey.

Key responsibilities include:

• Defining current-state, future-state, and transitional data architectures that support long-term business objectives.
• Developing strategic roadmaps that balance business value, risk, investment, and speed to market.
• Partnering with business and technology leaders to translate organizational priorities into scalable architecture solutions.
• Designing modern data platforms that support batch, near real-time, and real-time processing.
• Building and optimizing cloud-native data integration patterns across diverse source systems and applications.
• Architecting resilient, high-performance streaming platforms leveraging Apache Kafka and AWS-native services.
• Incorporating advanced AI capabilities including vector databases, Agentic AI frameworks, MCP, and RAG architectures to unlock new business opportunities.
• Championing infrastructure automation, CI/CD pipelines, and reusable architectural patterns that improve consistency and delivery velocity.
• Driving enterprise-wide best practices around data governance, security, quality, and lifecycle management.
• Providing architectural leadership, mentoring technical teams, and fostering a culture of innovation and continuous improvement.

Team Environment

You’ll join a highly collaborative, solution-oriented technology team that values innovation, knowledge sharing, and collective success. Team members are empowered to challenge conventional thinking, exchange ideas openly, and work together to solve complex business and technical challenges.

The culture encourages:

• Continuous learning and experimentation
• Cross-functional collaboration
• Technical excellence
• Mentorship and professional growth
• Innovation through emerging technologies

What We’re Looking For

Successful candidates will bring a blend of enterprise architecture expertise, cloud transformation experience, and a passion for modern data and AI technologies.

Preferred Qualifications

• Bachelor’s degree in Information Systems, Computer Science, Data Analytics, Engineering, or a related discipline.
• 15+ years of experience designing and delivering enterprise data solutions and modern data architectures.
• Deep expertise building cloud-native platforms within AWS.
• Proven experience developing data frameworks, reference architectures, operating models, and enterprise-scale integration patterns.
• Strong experience with streaming architectures, data modeling, and modern data platform design.
• Demonstrated success leading large-scale modernization and transformation initiatives.
• Familiarity with emerging AI architectures, including Agentic AI, vector databases, MCP, and RAG frameworks.
• Experience influencing senior stakeholders and leading enterprise architecture decisions.
• TOGAF certification or equivalent enterprise architecture framework experience preferred.

Ideal Candidate Profile

We’re seeking a strategic architect who is excited by transformation, energized by innovation, and motivated by the opportunity to build what comes next. This individual combines deep technical expertise with business acumen, communicates effectively with executive stakeholders, and enjoys mentoring teams while delivering meaningful outcomes at enterprise scale.

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