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Overview

A large, complex enterprise is seeking a senior data science leader to build and scale its data science function. This role is responsible for translating data into predictive, prescriptive, and AI-enabled insights that improve customer experiences, operational performance, decision-making, and organisational outcomes.
The Director, Data Science will lead teams focused on statistical modelling, machine learning, experimentation, forecasting, optimisation, decision support, and AI-enabled analytics. The position partners closely with data, engineering, product, digital, and business stakeholders to ensure analytical solutions are built on trusted data and deliver measurable value.
This leader will establish best practices for model development, validation, deployment readiness, monitoring, and lifecycle management while fostering a high-performance, innovation-focused culture.

Key Responsibilities

Data Science Strategy & Leadership

• Define and execute the enterprise data science roadmap aligned to strategic business priorities.
• Identify opportunities where advanced analytics, machine learning, optimisation, and AI can improve organisational outcomes.
• Prioritise investments based on business value, feasibility, data readiness, and strategic importance.
• Establish standards for experimentation, model development, validation, documentation, monitoring, and governance.
• Ensure solutions are scalable, reusable, interpretable where appropriate, and aligned with enterprise architecture and responsible AI principles.

Advanced Analytics, Machine Learning & AI

• Lead development of predictive, prescriptive, optimisation, and forecasting models across multiple business domains.
• Oversee customer segmentation, risk modelling, recommendations, personalisation, propensity modelling, and decision-support solutions.
• Partner with engineering and product teams to operationalise analytical capabilities within production environments and business workflows.
• Support AI initiatives by defining methodologies, evaluation approaches, and performance expectations.
• Promote modern statistical and machine learning techniques while ensuring appropriate application and risk management.

Model Evaluation, Experimentation & Measurement

• Define frameworks to evaluate model performance, business impact, reliability, fairness, and adoption.
• Lead experimentation strategies including A/B testing, causal inference, impact measurement, and test design.
• Collaborate with engineering, product, quality, and business teams on model monitoring and continuous improvement.
• Translate analytical outputs into actionable insights and business recommendations.
• Establish reporting, dashboards, and executive-level performance reviews.

Cross-Functional Collaboration

• Partner with enterprise data teams to ensure access to reliable, high-quality data.
• Collaborate with knowledge management, semantic modelling, and data product teams to improve analytical outcomes.
• Work closely with product, operations, technology, and business leaders to identify and prioritise analytical opportunities.
• Support production deployment of models and analytical services in partnership with engineering teams.
• Provide strategic guidance on where advanced analytics and AI can create value, and where alternative approaches may be more appropriate.

Team Leadership & Development

• Build, lead, and mentor a high-performing team of data scientists and analytics professionals.
• Define organisational structure, hiring strategy, capability development, and career progression pathways.
• Establish effective collaboration models across data, engineering, governance, product, and business teams.
• Coach team members on technical excellence, stakeholder engagement, communication, and business impact.
• Foster a culture of innovation, accountability, continuous learning, and responsible AI.

Required Qualifications

Education

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, Operations Research, Public Health, Informatics, or a related field.
• Master’s degree or PhD preferred.

Experience

• 12-18+ years of experience in data science, machine learning, advanced analytics, applied statistics, or related disciplines.
• 5-8+ years leading data science, analytics, or machine learning teams.
• Proven experience delivering analytical solutions that influence business or operational decision-making.
• Experience partnering with engineering, technology, product, and executive stakeholders.
• Strong background in model development, experimentation, monitoring, and production deployment.
• Experience within a regulated industry preferred.

Technical Expertise

• Deep expertise in statistical modelling, machine learning, predictive analytics, optimisation, experimentation, and decision science.
• Proficiency with Python, R, SQL, notebook-based development environments, and modern machine learning frameworks.
• Experience assessing data quality, feature readiness, model performance, bias, drift, interpretability, and operational fit.
• Understanding of model deployment, monitoring, integration, and lifecycle management within production environments.
• Familiarity with AI, Generative AI, large language model evaluation, recommendation systems, forecasting, personalisation, and decision-support methodologies.
• Strong knowledge of privacy, security, governance, and responsible AI practices.

Preferred Qualifications

• Experience leading data science teams within healthcare, life sciences, financial services, or other highly regulated industries.
• Experience supporting AI-enabled products, digital experiences, operational optimisation, workflow automation, or decision-support capabilities.
• Experience building reusable analytical frameworks and platforms that support multiple business functions.
• Experience defining enterprise standards for model evaluation, observability, monitoring, and continuous improvement.
• Familiarity with semantic models, ontologies, knowledge graphs, or enterprise knowledge management frameworks.
• Strong executive communication and stakeholder management skills.

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Director of Data Science
New York (Hybrid) – $240,000 – $300,000 + Bonus + Benefits

This is an opportunity to shape the future of enterprise Data Science within a large-scale, data-rich organisation undergoing significant AI and analytics transformation. You will lead a high-performing team, influence strategic decision-making at the highest level, and drive the development of advanced machine learning and AI solutions that deliver measurable business impact.

The Company
They are a well-established organisation with a strong commitment to innovation, data-driven decision-making, and digital transformation. Operating at enterprise scale, they are investing heavily in AI, machine learning, and advanced analytics to improve outcomes across multiple business functions.
With a collaborative and technology-focused environment, they empower teams to solve complex challenges using modern data capabilities. They offer the opportunity to work on meaningful initiatives with visibility across senior leadership and key stakeholders.

The Role
As Director of Data Science, you will be responsible for defining and delivering the organisation’s data science strategy while leading a team of highly skilled practitioners.
Responsibilities include:
* Develop and execute the enterprise data science roadmap aligned to strategic business priorities.
* Lead teams delivering predictive modelling, machine learning, optimisation, forecasting, experimentation, and AI-driven solutions.
* Partner with Product, Engineering, Data, and business stakeholders to identify high-value opportunities and translate them into scalable solutions.
* Establish best practices for model development, validation, monitoring, governance, and lifecycle management.
* Drive adoption of modern machine learning and AI methodologies while ensuring appropriate risk management and responsible AI principles.
* Oversee experimentation frameworks, performance measurement, and model evaluation approaches.
* Act as a trusted advisor to senior stakeholders, helping shape strategy through data-driven insights.
* Build, mentor, and develop a high-performing Data Science team and culture.

Your Skills & Experience
* Strong commercial experience leading Data Science, Machine Learning, or Advanced Analytics functions.
* Deep expertise in statistical modelling, predictive analytics, machine learning, experimentation, optimisation, and decision science.
* Strong experience developing and scaling production-grade data science solutions.
* Advanced proficiency with Python, SQL, and modern machine learning tools and frameworks.
* Experience working closely with engineering and product teams to operationalise analytical solutions.
* Strong stakeholder management skills with the ability to communicate complex concepts to technical and non-technical audiences.
* Experience building team capability, coaching talent, and driving delivery within a fast-paced environment.
* Understanding of AI governance, model monitoring, and responsible AI frameworks.

What They Offer
* Salary of $240,000 – $300,000 depending on experience.
* Performance-related bonus.
* Comprehensive healthcare and benefits package.
* Hybrid working environment.
* Opportunity to lead enterprise-scale AI and Data Science initiatives.
* Significant visibility with senior leadership and executive stakeholders.
* Clear scope for long-term career progression and organisational impact.

How to Apply
If you are an experienced Data Science leader looking to drive large-scale AI and analytics transformation, please apply today to learn more about this opportunity.

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Principal Data Scientist

Remote | Salary up to $220,000 + 15% bonus

This is an opportunity to step into a senior, high-impact Principal Data Scientist role where you will shape the direction of advanced AI and data science initiatives at scale. You will work on commercially meaningful problems, leveraging cutting-edge techniques including generative AI, while influencing both strategy and delivery across a globally recognised platform.

The Company
They are a well-established, innovation-led organisation focused on delivering data-driven products at scale. With a strong investment in AI and advanced analytics, they partner closely across product, engineering, and design to create impactful, user-focused solutions. Their teams are highly collaborative and operate in a modern, fully remote environment that encourages autonomy and technical excellence.

The Role

• Lead the design and implementation of advanced data science and AI solutions aligned to business objectives
• Provide technical leadership across complex projects, setting direction and best practice for modelling and deployment
• Collaborate with cross-functional stakeholders to identify opportunities and define requirements
• Apply generative AI and other advanced methodologies to solve real-world problems
• Translate technical findings into clear, actionable insights for senior stakeholders
• Oversee project timelines and ensure successful delivery across multiple workstreams

Your Skills and Experience

• Strong commercial experience in data science and machine learning, with recognised expertise in a specialist area
• Deep understanding of production-level AI systems and recent exposure to generative AI techniques
• Proven ability to lead complex projects end to end, from concept through to deployment
• Experience working cross-functionally with product, engineering, or business teams
• Clear and collaborative communication style, with the ability to influence senior stakeholders
• Background in a quantitative or technical field such as Data Science, AI, Mathematics, or similar

What They Offer

• Salary up to $220,000 with a 15% performance bonus
• Fully remote working with flexibility and autonomy
• Opportunity to work on high-impact AI initiatives at scale
• Collaborative, forward-thinking technical environment
• Clear scope for progression into broader technical or strategic leadership roles

How to Apply
If you’re interested in exploring this Principal Data Scientist opportunity, apply now for a confidential discussion.

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Lead Data Scientist

We are looking for a Lead Data Scientist to own complex quantitative and risk modeling projects from problem definition through implementation. This is a highly visible role where your models will directly influence multi-million-dollar business opportunities and be presented to executive stakeholders.

What You’ll Do

• Build, evaluate, and validate quantitative and risk models.
• Work with large financial and credit datasets.
• Develop models using Python, SQL, and gradient boosting techniques.
• Translate model outputs into measurable financial and dollar impact.
• Own projects end-to-end, from defining the problem through implementation.
• Present technical findings and recommendations to senior and executive stakeholders.
• Defend models and methodology during external audits.
• Help identify and quantify significant financial opportunities.
• Provide technical guidance and support to other team members.

What We’re Looking For

• 8+ years of data science/modeling experience
• Strong Python and SQL skills.
• Strong data modeling experience.
• Strong mathematical and statistical foundation.
• Experience with gradient boosting models.
• Proven ability to independently lead projects end-to-end.
• Excellent communication and presentation skills.
• Comfortable explaining technical work and model results to executives.
• Experience working through external audits and defending models.
• Finance/risk modeling experience within a regulated industry is required.

Required Domain Experience

You should have experience in areas such as:

• Credit risk modeling
• Financial or loss modeling
• Probability of Default (PD) modeling
• Credit scorecards
• Payment behavior modeling
• Credit attribute modeling
• Mortgage, credit card, banking, or credit bureau data
• Risk modeling within a regulated financial institution

Education

• Bachelor’s degree in Mathematics, Statistics, Economics, Computer Science, Quantitative Engineering, or another highly quantitative field.
• Master’s degree in Data Science or a related quantitative discipline preferred.

The Ideal Candidate

This role is suited to a senior-level Data Scientist who can operate independently, drive complex projects, and communicate confidently with both technical and executive audiences.

Location: Tempe, AZ preferred; Dallas or Atlanta also considered
Working Model: Hybrid, 4 days per week (Monday-Thursday)
Compensation: $140,000-$150,000 base
Visa: U.S. Citizen or Green Card holder only

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Senior AI Engineer
London (Hybrid)

A fantastic opportunity to join a world leading media company within a newly established AI Lab focused on building innovative Generative AI products. You’ll work in a small, high-impact team developing production-grade LLM applications that influence how users interact with content across text, audio, and emerging multimodal experiences.

The Company
A globally recognised organisation with a large international audience is investing heavily in AI innovation. Their dedicated AI Lab is exploring the future of AI-powered products, combining cutting-edge technology with real-world user impact. This is an opportunity to help shape the direction of a fast-growing function from an early stage.

The Role
You will:

• Build and fine-tune LLM-powered applications and services
• Develop and optimise RAG pipelines
• Deliver style and tone modelling solutions to improve LLM outputs
• Support personalisation, summarisation, and real-time generation initiatives
• Work closely with product, engineering, and business stakeholders
• Contribute to multimodal and audio-focused AI projects
• Help define evaluation frameworks and model quality standards

Your Skills & Experience

• Strong commercial experience building AI, NLP, or LLM-based products
• Hands-on experience with modern foundation models and AI frameworks
• Experience with fine-tuning, prompt engineering, or instruction tuning
• Strong Python engineering skills
• Experience evaluating and improving model performance
• Excellent communication skills and ability to work with non-technical stakeholders
• Experimental mindset and a passion for building high-quality AI products

Desirable experience includes speech technologies, generative audio, multimodal AI, or content-focused AI applications.

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Director of Data Science
Location: Remote | Salary: $260,000 to $300,000

This is an opportunity to lead AI and Data Science transformation within a large, mission-driven organisation that is investing heavily in improving customer experience through data. You’ll have the chance to shape strategy, build innovative solutions, and deliver tangible impact at enterprise scale.

The Company

They are a large, not-for-profit organisation operating at significant scale across a nationwide network of customer-facing services. With billions in annual revenue and millions of customer interactions each year, they are investing heavily in AI, machine learning, and next-generation digital experiences. Leadership views this area as a strategic priority, creating a genuine opportunity to influence enterprise-wide transformation.

The Role

• Lead a team of Data Scientists focused on customer journey and experience optimisation
• Define and execute the Data Science roadmap across customer, operational, and business priorities
• Build predictive, prescriptive, and optimisation models including personalisation, forecasting, segmentation, and recommendation solutions
• Develop semantic AI and conversational data products that power customer-facing applications, chat experiences, and digital tools
• Transform unstructured data from surveys, contact centre interactions, and customer touchpoints into actionable insights
• Partner closely with Data, AI Engineering, Product, Digital, and Operational teams to deploy solutions into production
• Establish best practices for model development, monitoring, governance, and business impact measurement

Your Skills & Experience

• Strong commercial experience leading Data Science, Machine Learning, or AI teams
• Proven track record delivering production-ready ML solutions that drive measurable business outcomes
• Expertise in predictive modelling, experimentation, personalisation, recommendation systems, and forecasting
• Experience working with unstructured, voice-of-customer, or text-based datasets
• Strong stakeholder management and executive communication skills
• Experience within healthcare or other regulated industries is beneficial but not essential
• Degree in a quantitative or STEM-related discipline, with advanced qualifications welcomed

What They Offer

• $260,000 to $300,000 base salary
• High-profile leadership role with executive visibility
• Opportunity to lead an established team of Data Scientists
• Significant investment in AI, GenAI, and customer-facing innovation
• The chance to solve meaningful customer experience challenges at enterprise scale

How to Apply

If you’re excited by the opportunity to combine AI leadership, customer experience transformation, and real-world impact, please apply to discuss this opportunity.

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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

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Staff Data Scientist (Product)

Location: Remote

Salary: $190-220k

We’re partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role embedded in their product organization. This is for someone who combines deep statistical expertise with the ability to influence how an entire company makes decisions – not just someone who runs experiments, but someone who builds the culture and infrastructure around them.

What You’ll Be Doing

• Owning and advancing the company’s experimentation roadmap, focused on high-leverage product questions around customer workflows, churn risk, and long-term value
• Designing and analyzing complex A/B tests, multivariate experiments, and Bayesian methods to measure the real impact of product changes
• Applying causal inference techniques (DiD, synthetic control, propensity score matching, instrumental variables) where traditional RCTs aren’t feasible
• Building and governing a unified KPI framework that connects product health metrics to meaningful business outcomes
• Partnering with Data Engineering to build scalable, self-serve experimentation tooling and reusable analytical frameworks
• Translating complex statistical findings into clear, compelling narratives for VP and C-suite audiences
• Mentoring and training junior and mid-level data scientists on experimental design and causal modeling

What We’re Looking For

This is a senior individual contributor role reporting to the Director of Product Data, acting as a strategic thought partner across Product, Engineering, Finance, Design, and Product Marketing. The company is at an inflection point in how it uses data to make product decisions, and this person will be central to shaping that.

Essential:

• 6+ years in applied data science, economics, or product analytics
• Proven expertise in causal inference: DiD, PSM, instrumental variables, quasi-experimentation
• Deep experience in A/B testing methodology including sequential testing, CUPED, variance reduction, and network effects
• Advanced SQL and Python or R for statistical modeling
• Experience with Snowflake or similar cloud data warehouses
• Exceptional communication skills, comfortable presenting to and influencing C-suite stakeholders
• Demonstrated ability to drive change in organizations where experimentation culture is still developing

Nice to have:

• Experience with dbt, Airflow, or Databricks
• Background in SaaS and product data science

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Staff GTM Data Scientist

Location: Remote

Salary: $190-220k base

We’re partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role sitting at the heart of their product and go-to-market strategy. This isn’t a reporting role or a dashboard-builder position. It’s for someone who can drive a genuine shift toward data-driven decision making across the organization, and who has the technical depth and communication skills to bring leadership along with them.

What You’ll Be Doing

• Owning and advancing the company’s experimentation roadmap, focusing on high-leverage questions around customer workflows, churn risk, and long-term value
• Designing and analyzing complex A/B tests, multivariate experiments, and Bayesian methods to assess the real impact of product and business changes
• Applying causal inference techniques (DiD, synthetic control, propensity score matching, instrumental variables) where traditional RCTs aren’t feasible
• Building and governing a unified KPI framework that connects product health metrics to business outcomes
• Partnering with Data Engineering to build scalable, self-serve experimentation tooling and reusable analytical frameworks
• Translating complex statistical findings into clear, compelling narratives for VP and C-suite audiences
• Mentoring and training junior and mid-level data scientists on experimental design and causal modeling

What We’re Looking For

This is a senior individual contributor role reporting to the Director of GTM Data, acting as a strategic thought partner across Product, Marketing, Finance, and Engineering. The company is at an inflection point in how it uses data, and this person will be central to shaping that.

Essential:

• 6+ years in applied data science, economics, or product analytics
• Proven expertise in causal inference: DiD, PSM, instrumental variables, quasi-experimentation
• Deep experience in A/B testing methodology including sequential testing, CUPED, variance reduction, and network effects
• Advanced SQL and Python or R for statistical modeling
• Experience with Snowflake or similar cloud data warehouses
• Exceptional communication skills, comfortable presenting to and influencing C-suite stakeholders
• Demonstrated ability to drive change in organizations where experimentation culture is still maturing

Nice to have:

• Experience with dbt, Airflow, or Databricks
• Background in SaaS and product data science

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