To Apply for this Job Click Here

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

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Scientist – Leicester or London 1 day a week

We are currently supporting a large insurance company on a Senior Data Science role to sit within their pricing team. This role will challenge core pricing functions and create innovative ways to produce new pricing models using larger and more complex data sources to deliver more competitive pricing and better customer accessibility. It’s a small, fast‑paced team (6 people) working on more experimental and forward‑thinking pricing approaches.

Some of the exciting work includes:

• Alternative pricing models
• Footprint modelling / Geospatial modelling
• Residual modelling to identify gaps between predicted vs. actual claim costs
• Working with large, messy insurance datasets across multiple product lines
• Tools & tech: Python, SQL, AzureML, XGBoost
• Opportunity to mentor within the team

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Scientist
London (Hybrid, 2 days per week)

This is an opportunity to join a high-impact data science function at a business undergoing a major AI transformation. You will play a key role in shaping how advanced machine learning and personalisation are embedded into customer products, driving measurable improvements in engagement, wellbeing, and long-term outcomes. The role offers strong ownership, exposure to senior stakeholders, and the chance to deliver production-grade AI at scale.

The Company
They are a large, well-established organisation operating in a highly data-rich, customer-focused environment. With a strong emphasis on innovation, they are investing heavily in AI and machine learning to enhance their product offering and create more personalised user experiences. Their data science teams operate in a collaborative, cross-functional model, working closely with engineering, product, and business stakeholders. The organisation promotes a culture of continuous improvement, experimentation, and responsible AI adoption.

The Role

• Lead the end-to-end delivery of data science and machine learning solutions, from scoping through to deployment and monitoring
• Design and build production-ready ML systems, including recommender systems, segmentation models, and optimisation solutions
• Translate complex business challenges into scalable, data-driven solutions with measurable impact
• Own technical delivery within a pod structure, guiding and mentoring other data scientists
• Collaborate with data engineering, software engineering, and product teams to deliver robust, scalable platforms
• Drive best practices in model deployment, version control, CI/CD, and performance monitoring
• Engage senior stakeholders to influence decision-making and support broader AI adoption across the business
• Contribute to the development of new AI-driven initiatives, including early-stage generative AI use cases

Your Skills & Experience

• Strong commercial experience in machine learning and data science, including regression and classification techniques
• Advanced Python and SQL skills, with a focus on building and deploying production-ready solutions
• Proven track record of delivering end-to-end data science projects in a business environment
• Experience working in cross-functional teams and collaborating with technical and non-technical stakeholders
• Demonstrated ability to lead projects, mentor others, and operate effectively in ambiguous environments
• Familiarity with modern ML tooling, version control, and deployment practices
• Exposure to cloud environments or generative AI is beneficial but not essential

To Apply for this Job Click Here

To Apply for this Job Click Here

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

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Scientist

London (Hybrid, 2 days onsite)

The Company
They are a large, established organisation operating at scale, with a strong focus on using data and AI to drive innovation across their products and services. The business is undergoing a significant AI transformation, with over ten active AI initiatives spanning areas such as automation, personalisation, and internal tooling. Their data science function is at the core of this journey, working closely with product and engineering teams to deliver tangible impact.
The environment is fast-paced and collaborative, with a strong emphasis on building production-ready AI solutions and embedding them into core business processes.

The Role
As a Senior Data Scientist, you will focus on delivering AI solutions that drive automation and efficiency across the organisation. You will take ownership of key projects and work across the full model lifecycle in a production environment.

• Lead the development and deployment of AI and machine learning solutions across multiple business areas
• Own and deliver end to end AI initiatives, from problem definition through to production
• Work on a range of use cases including internal chatbots, LLM applications, summarisation tools, underwriting automation, and AI sales assistants
• Collaborate with product managers and engineers to ensure solutions are scalable and aligned to business needs
• Implement and maintain MLOps best practices, including monitoring and model lifecycle management
• Engage with senior stakeholders, translating technical outputs into clear business value
• Contribute to the ongoing development of AI capability across the team

Your Skills and Experience

• Strong commercial experience in data science with a recent focus on AI and machine learning
• Proven experience building and deploying production-level AI solutions
• Experience working with GCP and modern cloud-based data environments
• Hands-on experience with MLOps, including deployment, monitoring, and scaling models
• Exposure to generative AI techniques such as LLMs and Retrieval Augmented Generation
• Strong stakeholder management and communication skills across technical and non-technical teams
• Experience working in larger, complex organisations with multiple concurrent workstreams

What They Offer

• Competitive pension scheme
• Private healthcare
• Hybrid working with two days per week in their London office
• Opportunity to work on high-impact AI initiatives with real business visibility
• Clear progression within a growing and strategically important team

How to Apply
If you are interested in applying your data science and AI expertise in a high-impact environment, please get in touch to learn more.

To Apply for this Job Click Here

To Apply for this Job Click Here

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

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff Data Scientist, Finance – Consumption Forecasting

Location: San Francisco or New York | Hybrid (3 days per week in office)

Salary: $240-300k base + bonus + equity (RSUs)

This is a rare chance to own forecasting infrastructure at the center of a high-growth, consumption-based developer platform, one that powers some of the world’s most dynamic applications and scales with every developer and enterprise building on it.

As a consumption-based business, forecasting usage across compute, bandwidth, edge, and storage isn’t a support function. It’s foundational to how we plan infrastructure, revenue, and long-term strategy. This role exists to lead that work at the highest level.

What you’ll own

This is a senior individual contributor role with organization-wide impact. You’ll define forecasting methodology, build systems that scale with a rapidly growing platform, and sit at the intersection of Finance, Infrastructure, Product, and GTM with direct visibility to executive leadership.

• Own production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration from first principles to live system
• Build forecasting systems that account for usage-based pricing dynamics, consumption patterns, and customer lifecycle across the platform, built for how this business actually works, not retrofitted SaaS models
• Design hierarchical forecasting models across account, cohort, segment, and global aggregate levels, covering operational, quarterly, and long-range planning cycles
• Establish backtesting, monitoring, and explainability standards that make forecast accuracy transparent and defensible
• Build scenario simulation frameworks to evaluate pricing changes, packaging adjustments, and product launches
• Partner with Finance on board-level reporting, with Infrastructure Engineering on capacity planning, and with Product and GTM on adoption curves and usage drivers
• Set forecasting best practices across the broader Data organization

What we’re looking for

• 7+ years in data science, quantitative analytics, or applied statistics at senior or staff level
• Deep expertise in time-series forecasting and statistical modelling in a usage-based or SaaS environment
• Proven track record building and productionizing ML systems at scale
• Strong Python and SQL, with experience on large-scale usage and billing datasets
• Familiarity with probabilistic modelling, hierarchical forecasting, and causal inference
• Experience partnering with Finance or executive leadership on planning cycles
• Comfortable operating autonomously in fast-moving, ambiguous environments

Nice to have

• Background in cloud infrastructure, developer tools, or consumption-based revenue models
• Familiarity with modern data stacks: Snowflake, Delta Lake, dbt, Airflow
• Prior technical mentorship or informal leadership experience

To Apply for this Job Click Here

To Apply for this Job Click Here

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

To Apply for this Job Click Here

To Apply for this Job Click Here

Principal Data Scientist
Full Remote (From the US)
Salary up to $210K base + bonus

A large, global technology-led organisation operating in a mission-driven, data-intensive domain. The business designs and scales complex digital platforms used by millions of end users worldwide, combining advanced data science, AI, and product engineering to drive measurable real-world impact.

Mission

• Act as technical lead for high-impact Data Science and AI initiatives across the organisation
• Define architectures, methodologies, and best practices for complex DS/AI and GenAI problem spaces
• Lead the design and delivery of production-grade AI systems, with particular focus on LLMs and generative AI
• Drive strategic initiatives by aligning DS/AI priorities with business and product objectives
• Mentor senior and junior data scientists, setting technical direction and raising engineering standards
• Own multiple projects simultaneously: scoping, prioritisation, delivery timelines, and stakeholder alignment

Profile

• PhD or equivalent in Data Science, Applied Mathematics, Statistics, or related field
• Senior-level experience: typically 6-10+ years in DS/AI roles, including leadership at Principal / Staff level
• Demonstrated technical leadership: defining strategy, owning complex initiatives, and mentoring teams
• Deep hands-on experience with production-scale DS/AI systems, with a strong recent focus on Generative AI / LLMs
• Expertise in LLM architectures, orchestration frameworks, and AI governance (guarding, scaling, monitoring, reliability)
• Strong understanding of MLOps / LLMOps in enterprise environments

To Apply for this Job Click Here