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Head of Data Science
London (Hybrid, 2 to 3 days per week)

This is a high-impact leadership opportunity to shape how a major consumer business uses data to drive growth, improve decision making, and deliver measurable value. You will lead the integration of data science and analytics into a single, high-performing function while influencing senior stakeholders and setting a clear strategic direction.

The Company
They are a well-established, customer-focused organisation undergoing a significant data transformation. With strong investment and leadership support, data is central to their future strategy. The business operates in a fast-paced, commercially driven environment and places high value on innovation, experimentation, and measurable outcomes. Data maturity is still developing, creating a genuine opportunity to shape the roadmap and drive meaningful change.

The Role
You will take ownership of the data science and analytics capability, focusing on both strategy and execution. Key responsibilities include:
* Defining and delivering the data science and analytics strategy aligned to wider business goals
* Driving the adoption of self-serve analytics tools and improving data accessibility across teams
* Leading the redesign and optimisation of reporting, dashboards, and insight delivery
* Overseeing development, productionisation, and deployment of data science solutions
* Embedding performance frameworks to measure value, impact, and business outcomes
* Building and scaling a high-performing, multidisciplinary team across data science and analytics
* Engaging and influencing senior stakeholders, including CIO and COO level
* Shifting perception of data science from a support function to a core value driver

Your Skills and Experience
You will bring a strong combination of technical depth, leadership capability, and commercial awareness:
* A background as a data scientist with strong attention to detail and the ability to challenge methodologies
* Deep understanding of data science techniques, principles, and underlying mathematics
* Strong experience delivering data science solutions across multiple domains in commercial settings
* Proven ability to build, develop, and lead high-performing teams
* Experience operating in environments with low or evolving data maturity
* Excellent stakeholder management skills, with the ability to translate complex concepts into clear business narratives
* Strong track record of delivering measurable business impact from data initiatives
* Comfortable working in ambiguous, fast-changing environments and driving transformation

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Graduate Data Scientist

London – 4 days a week

The Company
They are a modern, data-driven insurance provider focused on delivering flexible, tailored policies to customers. The business has expanded its product offering and built strong commercial partnerships, driving rapid growth. With around 100 employees, they are scaling quickly and investing heavily in advanced analytics and modelling. The culture is collaborative, fast-paced, and centred on innovation.

The Role
As a Graduate Data Scientist, you will work on models that sit at the core of the business and support key commercial decisions.

• Develop predictive models across pricing, risk, and customer acquisition
• Build clustering and segmentation models to support strategic decision-making
• Analyse large and complex datasets to uncover actionable insights
• Collaborate with analysts and engineers to deploy and productionise models
• Contribute to a greenfield modelling environment and help shape best practices
• Take ownership of projects with visibility across the wider business

Your Skills and Experience

• Strong academic background in a STEM subject such as Mathematics, Data Science, Computer Science, or similar
• Solid programming skills, ideally in Python
• Understanding of statistical modelling and machine learning fundamentals
• Hands-on experience through internships, placements, or personal projects
• Demonstrated curiosity and initiative, such as side projects or GitHub work
• Clear communication skills and the ability to collaborate with cross-functional teams
• Motivated, proactive, and keen to take ownership early in your career

What They Offer

• Hybrid working with a strong in-office culture
• Opportunity to work on high-impact, business-critical models
• Fast career progression as the team continues to grow
• Work abroad flexibility for short periods each year
• Supportive environment with strong learning and development opportunities

How to Apply
If you are a graduate or early-career data scientist looking to make an impact in a high-growth environment, please apply with your CV.

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Graudate Data Science Role

This is an excellent opportunity to join a fast-growing, data-driven insurance business that is transforming how pricing and risk are approached. With strong investment in analytics and a high-performing team already in place, you will have the chance to work on impactful pricing problems while developing your skills in a highly commercial environment.
You will join the pricing team, playing a key role in analysing customer data and supporting pricing strategy.

The Role:

• Develop and refine pricing models to optimise customer acquisition and retention
• Analyse large datasets to identify trends and inform commercial decisions
• Collaborate with stakeholders to translate business requirements into data solutions
• Contribute to model development and testing within a regulated environment
• Support ongoing improvement of pricing processes and methodologies
• Work in a fast-paced team, delivering insights with real business impact

Your Skills and Experience

• Strong academic background in a quantitative discipline such as Mathematics or Physics
• Proven ability to work with data and build analytical models
• Experience or interest in pricing, insurance, or closely related commercial analytics
• Strong problem-solving skills, with the ability to think logically and clearly
• Comfortable communicating technical ideas to non-technical stakeholders
• Strong attention to detail and a structured approach to analysis

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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 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 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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Senior Data Scientist – Growth & Customer Analytics

Remote – US

Compensation up to 200K

We are seeking a Senior Data Scientist to help drive customer growth, retention, and lifecycle optimization through advanced analytics and machine learning.

This role sits at the intersection of Data Science, Product, Marketing, and Customer Success, leveraging data to improve customer acquisition, engagement, retention, and expansion strategies. The successful candidate will play a key role in developing predictive models, customer segmentation frameworks, and experimentation strategies that directly influence business performance.

Responsibilities:

• Develop and deploy predictive models focused on customer churn, retention, expansion, and lifetime value
• Build customer segmentation frameworks to better understand user behavior and support personalized engagement strategies
• Partner closely with Marketing, Product, Revenue, and Customer Success teams to identify growth opportunities and optimize customer journeys
• Analyze customer lifecycle performance and identify opportunities to improve acquisition, activation, engagement, retention, and expansion metrics
• Design and evaluate A/B tests and experiments to measure the effectiveness of marketing campaigns, product initiatives, and customer engagement programs
• Translate complex analytical findings into actionable recommendations for both technical and non-technical stakeholders
• Develop forecasting models and business insights that support strategic decision-making
• Collaborate with Data Engineering and Analytics teams to ensure scalable and reliable data solutions
• Influence business strategy through data-driven insights and measurable outcomes.

Requirements

• Master’s or PhD in Statistics, Mathematics, Data Science, Computer Science, Economics, Operations Research, or a related quantitative discipline
• 4+ years of experience in Data Science and Applied Machine Learning, alongside areas like Customer Analytics, Marketing Analytics, or a related field
• Strong experience building predictive models focused on churn prediction, customer retention, customer lifetime value, propensity modeling, or expansion opportunities
• Expertise in customer segmentation techniques, clustering methodologies, and behavioral analytics
• Strong understanding of experimentation, causal inference, and statistical analysis
• Advanced proficiency in Python and SQL
• Experience working with large-scale customer and transactional datasets
• Ability to communicate insights and recommendations to both technical and business stakeholders
• Experience supporting growth, marketing, customer success, or product organizations is highly desirable

Preferred Experience

• Experience in SaaS, subscription-based businesses, marketplaces, fintech, consumer technology, or digital products
• Familiarity with machine learning frameworks such as Scikit-Learn, XGBoost, PyTorch, or TensorFlow
• Experience with cloud platforms such as AWS, GCP, Azure, or Databricks
• Knowledge of customer journey analytics, attribution modeling, and marketing measurement frameworks

What You’ll Impact

• Customer Retention & Churn Reduction
• Customer Lifetime Value (CLV) Optimization
• Expansion & Upsell Opportunities
• Marketing Performance & Campaign Effectiveness
• Customer Segmentation & Personalization
• Growth Strategy & Revenue Acceleration

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Founding Data Scientist
NYC (5 Days Onsite – Midtown)
Up to $240K Basic Salary

We’re partnered with an early-stage company operating at the intersection of data, trading, and live events, looking to hire a Founding Data Scientist to help build and scale their core pricing and bidding systems.

This is an opportunity to join a small, high-caliber team where your work will directly influence pricing decisions, inventory strategy, and revenue generation.

What you’ll be working on:
* Pricing and inventory models in a real-time marketplace
* Bidding and trading algorithms
* Machine learning systems used in production
* Model evaluation and performance optimization
* Scaling core data science capabilities from the ground up

What they’re looking for:
* Strong background in machine learning and data science
* Experience building and deploying models into production
* Advanced Python and SQL skills
* Experience working in fast-paced, high-growth environments
* Someone who enjoys solving complex commercial problems

This is a rare opportunity to join at an early stage and help shape both the technical direction and future growth of the business.

Apply below or reach out directly for a confidential conversation.

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