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Clinical Data Scientist
San Francisco, California

Remote

$160,000 – $190,000 + Equity

About the Company

This innovative health tech startup is working to improve the oncology drug development process by providing better patient data to drug developers as well as better access to clinical trials for patients. This series B startup is expending to meet demand.

About the Role

As a Clinical Data Scientist, you’ll execute the last leg of the clinical data pipeline by transforming, cleaning, validating, and delivering high‑quality clinical datasets for pharma partners. Heavy collaboration with Clinical Ops, AI Engineering, and Data Delivery.

Role Responsibilities

• Transform raw, abstracted, and AI‑processed data into CDISC SDTM/ADaM datasets
• Program statistical outputs (tables, listings, figures) in SAS/R/Python
• Investigate data anomalies across multiple messy data inputs
• Define data dictionaries and standards before study kickoff
• Handle data in a HIPAA‑aligned manner

Key Requirements

• 2-5 years in clinical data science, stat programming, or clinical data management
• Pharma/Biotech experience
• SAS, R, Python, SQL
• Real‑world clinical data or oncology trials
• CDISC SDTM/ADaM

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Senior Data Scientist

£60,000 – £75,000

London or Leicester (1 day a week in office)

This is an opportunity to join a highly regarded data science function where innovation sits at the centre of decision making. Working within a specialist pricing team, you will have the freedom to explore new data sources, develop cutting-edge machine learning models, and shape how customer risk is assessed across a large-scale digital business. If you enjoy solving complex problems and building impactful models from messy, high-volume datasets, this role offers both technical challenge and visibility.

THE COMPANY

They are a market-leading digital organisation with a strong reputation for using data and analytics to drive business performance. Having invested heavily in their data science capabilities, they continue to expand a high-performing analytics community that values curiosity, experimentation, and collaboration.

THE ROLE

As a Senior Data Scientist you will join a specialist team focused on developing innovative approaches to customer risk assessment and pricing.

Specifically, you can expect to be involved in the following:

• Building and deploying predictive machine learning models that improve pricing and customer selection strategies
• Exploring and evaluating new data sources to identify commercial opportunities
• Developing geospatial and footprint models using alternative datasets
• Creating residual and claims-related models to improve business performance
• Working with large, complex, and often unstructured datasets
• Taking ownership of projects from problem definition through to delivery
• Mentoring and supporting junior team members

SKILLS AND EXPERIENCE

The successful Senior Data Scientist will have the following skills and experience:

• Strong commercial experience delivering machine learning and predictive modelling projects
• Advanced Python and SQL skills
• Experience working with large and complex datasets
• Knowledge of machine learning techniques such as XGBoost, CatBoost, or related models
• Experience working in cloud-based environments, ideally Azure
• Strong stakeholder management and communication skills
• Ability to translate business challenges into analytical solutions
• Experience within insurance is valuable but not essential

BENEFITS

The successful Senior Data Scientist will receive the following benefits:

• Salary between £60,000 – £75,000 – depending on experience
• £5000 annual car allowance
• Performance bonus scheme with on-target bonus and enhanced earning potential
• 10% matched pension contribution
• 27 days annual leave plus bank holidays
• Private medical insurance
• And other benefits

HOW TO APPLY

Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Scientist

£60,000 – £75,000

London or Leicester (1 day a week in office)

This is an opportunity to join a highly regarded data science function where innovation sits at the centre of decision making. Working within a specialist pricing team, you will have the freedom to explore new data sources, develop cutting-edge machine learning models, and shape how customer risk is assessed across a large-scale digital business. If you enjoy solving complex problems and building impactful models from messy, high-volume datasets, this role offers both technical challenge and visibility.

THE COMPANY

They are a market-leading digital organisation with a strong reputation for using data and analytics to drive business performance. Having invested heavily in their data science capabilities, they continue to expand a high-performing analytics community that values curiosity, experimentation, and collaboration.

THE ROLE

As a Senior Data Scientist you will join a specialist team focused on developing innovative approaches to customer risk assessment and pricing.

Specifically, you can expect to be involved in the following:

• Building and deploying predictive machine learning models that improve pricing and customer selection strategies
• Exploring and evaluating new data sources to identify commercial opportunities
• Developing geospatial and footprint models using alternative datasets
• Creating residual and claims-related models to improve business performance
• Working with large, complex, and often unstructured datasets
• Taking ownership of projects from problem definition through to delivery
• Mentoring and supporting junior team members

SKILLS AND EXPERIENCE

The successful Senior Data Scientist will have the following skills and experience:

• Strong commercial experience delivering machine learning and predictive modelling projects
• Advanced Python and SQL skills
• Experience working with large and complex datasets
• Knowledge of machine learning techniques such as XGBoost, CatBoost, or related models
• Experience working in cloud-based environments, ideally Azure
• Strong stakeholder management and communication skills
• Ability to translate business challenges into analytical solutions
• Experience within insurance is valuable but not essential

BENEFITS

The successful Senior Data Scientist will receive the following benefits:

• Salary between £60,000 – £75,000 – depending on experience
• £5000 annual car allowance
• Performance bonus scheme with on-target bonus and enhanced earning potential
• 10% matched pension contribution
• 27 days annual leave plus bank holidays
• Private medical insurance
• And other benefits

HOW TO APPLY

Please register your interest by sending your resume to Majid Latif via the Apply link on this page.

To Apply for this Job Click Here

To Apply for this Job Click Here

I’m hiring a Senior Data Scientist to join a leading UK insurer’s Pricing & Data Science function, working on innovative machine learning solutions that directly influence risk assessment, pricing, fraud detection, and commercial performance.

This is a role for someone who enjoys taking models from problem definition through to deployment, working with modern ML techniques and real-world commercial challenges.

What you’ll be doing

• Build and deploy predictive models across pricing, claims, fraud, and risk analytics.
• Engineer new data assets and rating factors to improve pricing performance.
• Identify and leverage new data sources to drive business value.
• Partner with stakeholders across Pricing, Data Science, Analytics, and Engineering teams.
• Own ML projects end-to-end, including EDA, deployment, monitoring, and model refreshes.

What they’re looking for

– Proven experience delivering ML projects from concept to deployment.
– Strong Python and SQL skills.
– Experience with Azure ML, Git, and cloud-based analytics environments.
– Strong stakeholder engagement and commercial problem-solving capability.
– Passion for applying emerging ML techniques to real business problems.

Why join?

• Work in a highly respected pricing and analytics function.
• Bonus scheme + £5k car allowance.
• Private medical cover and strong benefits package.
• Opportunity to work on innovative modelling and pricing challenges at scale.

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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, Pricing
London| Competitive Salary up to £75,000 + Bonus + Car Allowance
This is an opportunity to join a highly data-driven organisation where pricing, analytics, and machine learning sit at the heart of business strategy. You will work on innovative data science initiatives that directly influence risk assessment, pricing decisions, and commercial performance, while helping to shape the next generation of predictive modelling capabilities.
The Company
They are a well-established consumer-focused organisation undergoing significant investment in data, analytics, and technology. With a strong emphasis on innovation, they use advanced machine learning and predictive modelling to support strategic decision-making and deliver better customer outcomes.
Their analytics community brings together Data Scientists, Analysts, and Data Engineers who collaborate to solve complex business challenges. They foster a culture of curiosity, continuous improvement, and knowledge sharing, creating an environment where new ideas are encouraged and valued.
The Role
You will play a key role in building and deploying advanced machine learning solutions that support pricing and risk decision-making.
Responsibilities include:

• Developing predictive models focused on risk, claims outcomes, fraud detection, and other key business metrics.
• Creating and maintaining analytical tools that improve portfolio management and commercial performance.
• Identifying, evaluating, and extracting value from new internal and external data sources.
• Engineering new features and rating factors to enhance existing pricing algorithms.
• Managing the full machine learning lifecycle, from exploratory analysis through to deployment, monitoring, and model refresh activities.
• Working closely with Data Scientists, Data Engineers, Analysts, and business stakeholders to translate challenges into impactful solutions.
• Exploring emerging machine learning techniques and assessing their commercial application.

Your Skills & Experience

• Strong commercial experience delivering machine learning projects from initial exploration through to deployment and ongoing optimisation.
• Advanced Python and SQL skills.
• Experience with Azure Machine Learning, Azure cloud technologies, and Git.
• Proven ability to communicate technical concepts to a range of stakeholders and influence decision-making.
• Experience working across multidisciplinary data and analytics teams.
• Strong problem-solving capabilities and a track record of delivering high-quality analytical solutions.
• An interest in applying innovative data science techniques to real-world business challenges.

What They Offer

• Competitive salary package.
• Annual performance bonus.
• Car allowance.
• Hybrid and flexible working arrangements.
• Private medical insurance.
• Generous pension contributions and life assurance.
• Income protection and a broad range of financial wellbeing benefits.
• Employee assistance and wellbeing support programmes.
• 27 days annual leave plus bank holidays, with additional flexibility options.
• Ongoing training, development, and clear opportunities for career progression within a growing data science function.

How to Apply
If you are a Senior Data Scientist with strong machine learning expertise and a passion for solving commercial problems through advanced analytics, apply today to discuss this opportunity in more detail.

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Data Scientist
London or Leicester (2 days per week)

Join a growing Data Science team where you’ll build machine learning solutions that directly influence customer engagement, retention, and commercial performance. This is a highly visible role with significant stakeholder exposure and the opportunity to work on both strategic initiatives and high-impact business challenges.

The Role

• Build and improve machine learning models focused on retention, engagement, customer lifetime value, and forecasting
• Develop anomaly detection solutions to identify issues impacting customer journeys and performance
• Design and evaluate experiments, including A/B testing
• Partner with Product, Marketing, Finance, CRM, and Commercial teams to solve business problems
• Translate complex analysis into actionable recommendations for stakeholders

Your Skills & Experience

• Strong commercial Data Science experience in customer, marketing, ecommerce, loyalty, or subscription environments
• Advanced Python and SQL skills
• Experience building predictive models and deploying data-driven solutions
• Strong understanding of experimentation, statistics, and machine learning
• Excellent stakeholder management and communication skills
• Experience with Databricks and ML lifecycle tools is beneficial

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