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Senior Decision Scientist
Brighton (Hybrid), Competitive Salary
This is an opportunity to join a highly data-driven, product-led organisation where analytics and AI are central to shaping commercial decisions and customer experience. As part of a growing data function, you will play a key role in embedding data into product development and driving measurable business impact.
The Company
They are an established and fast-growing digital platform operating at scale across international markets. The business is investing heavily in data, AI, and product innovation, with a strong focus on using insight to drive commercial performance.
Their data function is evolving into a hub-and-spoke model, embedding decision-focused data professionals directly into product teams. This creates a collaborative environment where data has real influence on strategy, product direction, and customer outcomes.
The Role
You will sit within a cross-functional product squad, acting as the data expert responsible for turning insight into action. Your work will shape product decisions, quantify impact, and drive continuous improvement. Responsibilities include:

• Acting as the data lead within a product squad, influencing decisions from planning through to delivery
• Identifying and sizing opportunities to improve product performance and customer experience
• Analysing customer journeys to uncover friction points, conversion drivers, and growth opportunities
• Defining success metrics and building dashboards to track performance
• Designing and running experiments, including A/B testing and statistical analysis
• Developing data-driven features, insights, and lightweight models where appropriate
• Communicating findings clearly to stakeholders, driving actionable recommendations
• Leveraging AI tools and modern analytics approaches to accelerate insight generation

Your Skills and Experience

• Strong commercial experience in analytics, data science, or product analytics roles
• Advanced SQL skills and experience with Python or R for analysis and experimentation
• Experience working with product, engineering, or commercial stakeholders in a collaborative environment
• Strong understanding of experimentation, hypothesis testing, and statistical analysis
• Ability to translate complex data into clear business recommendations
• Experience working with large datasets and modern data platforms
• Interest in AI and emerging technologies, with practical exposure to applied use cases
• A proactive and curious mindset, with the ability to work effectively in ambiguous environments

What They Offer

• Competitive salary and benefits package
• Hybrid working with a collaborative team environment
• Strong focus on learning and development, including dedicated time and resources
• Opportunity to work on impactful, business-critical projects
• Clear progression opportunities within a growing data function
• Exposure to cutting-edge tools, AI-driven workflows, and product innovation

How to Apply
Please apply with your CV to be considered for this opportunity.

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Senior Decision Scientist

London – hybrid – 3x a week

The Company
They are a global, technology driven marketplace operating across multiple regions, with a strong focus on sustainability and circular commerce. The business has experienced significant growth and continues to invest heavily in product, data and AI capabilities. Data sits at the heart of their strategy, with a mature data platform, strong documentation practices and increasing use of AI assisted analytics. They are evolving their data function into a hub and spoke model, embedding decision making closer to product teams.

The Role
You will operate at the intersection of analytics, product and commercial strategy, helping the business identify the right problems to solve and quantify impact. Key responsibilities include:

• Defining and scoping business problems with a strong commercial lens
• Opportunity sizing and identifying areas to drive revenue, efficiency or customer experience improvements
• Leading product analytics and supporting product squads with insight driven recommendations
• Designing experiments, defining success metrics and measuring A B testing outcomes
• Collaborating with analytics engineering and contributing to the wider data ecosystem
• Applying light touch data science where appropriate, such as segmentation or recommendation logic
• Influencing stakeholders across product, data and commercial teams to support decision making

Your Skills and Experience

• Strong commercial experience in data science within a product led environment
• Ability to translate ambiguous business challenges into structured analytical approaches
• Experience in product analytics, experimentation and performance measurement
• Confidence working with stakeholders and influencing decision making
• Exposure to statistical methods, modelling or machine learning concepts
• Comfortable balancing analytical rigour with pace and prioritisation
• Interest in AI, emerging analytics tools and data driven product development

What They Offer

• Competitive salary and comprehensive benefits package
• Clear progression opportunities as the team scales and embeds into product squads
• Exposure to a modern data and AI environment with strong foundations
• A collaborative culture focused on impact, learning and innovation
• The opportunity to shape how data drives commercial decisions in a growing organisation

How to Apply
If you are interested in applying analytics and data science to solve meaningful business problems and drive measurable impact, please get in touch to learn more.

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Data Scientist / Senior Data Scientist – Experimentation and Causal Inference

This is a high impact opportunity to join a newly formed team focused on using causal inference and experimentation to drive smarter decision making.

The Company

They are a global, data driven organisation investing in advanced experimentation and analytics. The business is building a specialist team to improve how experimentation informs commercial and product strategy. You will work in a collaborative, research led environment with real business impact.

The Role

• Lead deep dive analysis on experimentation, including cannibalisation and value decomposition
• Apply causal inference to identify true impact and drivers of change
• Evaluate experiments using counterfactuals and off policy approaches
• Build simulation tools to assess experiments before launch
• Partner with product and commercial teams to shape strategy

Your Skills and Experience

• Strong experience in experimentation and causal inference
• Background in Economics, Statistics, or a related field
• Solid grounding in econometrics and A B testing
• Experience with counterfactual analysis or simulation methods
• Proficiency in Python or R and SQL

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Job Description

Brain Labs – Director of Data Science

WFH – 3x a week in Old Street
Salary – up to £80,000 (no bonus)
Sponsorship – No (could look at someone with 2 years left on Visa if they are really strong, however the ideal is for someone to stay long term so ideally British citizens)

Team

• Most data capability has historically been in the India office
• Now decided to close and bring over to UK and build out a function here
• The purpose of this person will be to help grow the capabilities for the business
• Will report into Head of Data – Paul Wilmore
• Will manage the Junior DS Manager that we are also hiring for

Company

• Media agency that focuses on answering one question – what’s actually driving profit?
• Founded in 2012, they now have over 1000 employees across 5 continents
• They have their own proprietary agents, have built 32 media tools and have conducted 2500 experiments for their clients

Role

• Core remit of the role is focused on MMM – doing lots with google meridian as a business
• Implementing google MMM models for clients
• Need to be comfortable with opensource framework – meridian, robyn, piemc etc.
• Own the client delivery of MMM models from scratch – need to understand the whole process
• Know what goes into the model – understand good model vs a bad one
• 60% hands-on work vs 40% on the actual strategy – as team grows this will vary quite a lot
• Liasing and working directly with clients on delivery and strategy
• Work will vary a lot day to day between hands-on and strategic work (3 live clients at the moment) with pitches ongoing

What They Offer

• Salary up to £80,000
• Hybrid working with a London office
• Private healthcare, pension, and wellbeing support
• Generous holiday allowance and additional benefits
• Opportunity to shape and grow a data science function
• Clear progression into senior leadership as the team expands

How to Apply
Apply with your CV to be considered for 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 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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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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Are you a Data Scientist who enjoys building real‑world models that drive commercial decisions, not just experimentation? I’m hiring for a Data Scientist to join a leading data and analytics consultancy working across customer insight, marketing, and predictive modelling.

This is a brilliant opportunity to work on high‑impact data products, combining advanced analytics, business understanding, and client‑facing delivery in a collaborative, product‑focused environment.

The company

This is a well‑established data consultancy that sits at the intersection of data provision, analytics, and product development. They work with high‑volume customer data across sectors like utilities, telecoms, financial services, and charities – using data to solve real commercial problems and drive better decisions.

They’ve built out a Customer Intelligence Platform, where data science, analytics, and product teams collaborate to create scalable, reusable data products.

Where you fit

You’ll sit within the Data Science team, working closely with Product Managers, Data Analysts, and subject‑matter experts.

This is a hands‑on modelling role with strong client interaction, where you’ll take problems from discovery through to delivery – combining technical expertise with commercial thinking.

What you’ll be doing

• Build predictive models (often propensity modelling / scoring models) to solve real customer and business problems
• Work directly with clients to understand challenges, run discovery sessions, and shape analytical approaches
• Develop and refine models, including training, testing, and optimisation
• Lead rapid prototyping and proof‑of‑concept work using Databricks notebooks
• Define features, model structures, and scoring outputs for data products
• Translate analytical outputs into clear, actionable insights and presentations for clients
• Contribute to the development of scalable, reusable data products within the platform

Example project

You might build a model that predicts which customers are most likely to repay debt, then segment them to determine the best engagement strategy – using behavioural and demographic patterns to optimise outcomes.

Tech stack

• Python & SQL (essential)
• Databricks (core analytics environment)
• Azure‑based data platform (with flexibility depending on client environments)

What you bring

Must‑haves

• 3+ years experience in data science
• Strong Python and SQL skills
• Experience building and evaluating predictive models
• Understanding of data modelling and feature engineering
• Ability to translate data into clear commercial insight and recommendations
• Confident communicator – comfortable working directly with clients
• Consultancy or client‑facing experience

Nice to have

• Experience with Databricks or cloud platforms (Azure, etc.)
• Background in customer, marketing, or transactional data
• Exposure to industries like telecoms, financial services, or utilities

Why this role

• Work on end‑to‑end data science projects – not just isolated modelling
• Strong balance of technical work and commercial impact
• Opportunity to contribute to product development and innovation
• Exposure to multiple clients, industries, and use‑cases
• Collaborative team environment with analysts, SMEs, and product teams

Working pattern

• Hybrid: 1 day per week in London
• Open to candidates based in the Midlands who can commute weekly
• Additional flexibility for the right candidate
• UK travel to clients may be required depending on project work

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Principal Data Scientist

Location: Remote (USA)
Compensation: $200,000 – $250,000 Base Salary

About the Role

We’re hiring a Principal Data Scientist to join a growing team focused on building advanced machine learning solutions that improve decision-making, operational efficiency, and product intelligence across the business.

This is a senior individual contributor role for someone who enjoys solving complex, ambiguous problems and building scalable data science solutions from concept through production. You’ll work across large datasets, design robust modeling frameworks, and help shape the future of AI-driven decision-making within the organization.

This role offers high visibility, technical ownership, and the opportunity to influence both strategic and operational outcomes.

What You’ll Do

Machine Learning & Advanced Analytics

• Design, develop, and deploy machine learning models to solve complex business challenges
• Apply statistical analysis, predictive modeling, optimization techniques, and natural language processing to large-scale business problems
• Build and improve models focused on forecasting, classification, behavioral modeling, and operational optimization
• Evaluate model performance and continuously improve based on measurable business outcomes
• Develop experimental frameworks to test and validate model effectiveness

Data Infrastructure & Modeling

• Build and maintain robust SQL pipelines and ETL workflows to support model training and analytics
• Work across cloud-based and distributed data systems to access, transform, and prepare structured and unstructured data
• Conduct exploratory analysis, feature engineering, and anomaly detection to improve model quality
• Partner with data engineering teams to improve data reliability, accessibility, and scalability

Business Partnership

• Work closely with Product, Engineering, Operations, and Leadership teams to identify opportunities for machine learning applications
• Translate business challenges into scalable analytical frameworks and production-ready solutions
• Communicate technical findings and recommendations clearly to stakeholders at all levels

Technical Leadership

• Help establish best practices across experimentation, modeling, and deployment workflows
• Mentor other data scientists and support technical development across the team
• Stay current on emerging machine learning techniques and identify opportunities to apply them to business challenges

What We’re Looking For

• 10+ years of experience in Data Science, Machine Learning, or Advanced Analytics
• Strong expertise in Python and SQL
• Deep experience in statistical modeling, machine learning, and predictive analytics
• Experience deploying machine learning models into production environments
• Strong understanding of cloud data platforms and distributed computing frameworks
• Experience working with large-scale datasets and building reliable ETL workflows
• Familiarity with modern AI/ML tooling and generative AI applications
• Strong communication skills and the ability to work cross-functionally across technical and business teams
• Proven ability to influence strategy through data-driven insights

Preferred Qualifications

• Experience working in healthcare, life sciences, fintech, or other highly regulated environments
• Experience with NLP, recommendation systems, or optimization models
• Exposure to AWS and modern cloud-native data ecosystems
• Prior mentoring or leadership experience within Data Science teams

Why Join?

You’ll join a team where data science is a core driver of innovation and decision-making. This is an opportunity to work on meaningful, high-impact problems, build production-grade machine learning systems, and shape how advanced analytics are used across the business.

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