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The Company
We’re partnered with a fast-growing, product-led SaaS company where data plays a central role in product decision-making. The data team works closely with senior leadership and is continuing to scale.

The Role
This is a Staff-level individual contributor role within the Product Analytics team, focused on owning and scaling the company’s experimentation framework.

The organization is continuing to build its experimentation maturity, and this hire will play a key role in strengthening both the technical implementation and adoption of experimentation across the business.

You will act as a technical anchor for the team, ensuring robust statistical practices while working closely with stakeholders to support data-informed product decisions.

Key Responsibilities

• Own and scale the experimentation roadmap across product teams
• Design and implement robust experimentation frameworks (e.g., Bayesian methods, sequential testing)
• Apply causal inference to user behavior, feature adoption, retention, and churn
• Partner with product and engineering teams to ensure experiments are correctly designed and implemented
• Provide guidance to team members on advanced statistical methods
• Work with stakeholders to support adoption of experimentation best practices
• Evaluate and support implementation of experimentation tooling

Requirements

• 6+ years of experience in Data Science or Product Analytics
• Strong experience with experimentation (A/B testing, Bayesian methods, or similar approaches)
• Solid understanding of causal inference
• Experience working in SaaS product environments
• Ability to work with a high level of ownership and collaborate effectively with stakeholders

Technical Skills

• Python
• SQL
• Experience working in shared code environments (e.g., GitHub)

Nice to Have

• Experience evaluating or implementing experimentation platforms
• Exposure to modern AI-assisted tools (e.g., Cursor, Claude Code)

Additional Information

• Opportunity to contribute to the development of experimentation practices within a growing product organization
• High-visibility role with direct impact on product decision-making
• Fully remote within the US, aligned to EST working hours

Eligibility
Applicants must have the right to work in the United States. Sponsorship is not available.

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Role Title: Staff Data Scientist, Go-To-Market

Compensation: $180,000 – $210,000 USD Base

Location: United States (Remote)

The Opportunity

We’re partnering exclusively with a fast‑growing B2B SaaS company to hire a Staff Data Scientist who will play a central role in shaping how data drives customer growth, retention, and revenue strategy. The business is at an inflection point, intentionally moving from descriptive analytics toward predictive, model‑driven decision making across its go‑to‑market organization.

This is a rare opportunity to step into a high‑impact, senior individual contributor role where the models you build directly influence how teams prioritize accounts, engage customers, and allocate resources.

About the Role

The team is looking for a Staff Data Scientist who can operate across two complementary problem spaces. The first is predictive customer analytics: building robust models for churn, retention, expansion, and early‑lifecycle lifetime value. The second is stakeholder‑embedded problem solving: translating ambiguous commercial questions into scalable data science solutions that teams actually use.

This role is intentionally hands‑on and model‑heavy. You’ll own work from problem framing and feature discovery through model development, validation, and production handoff. While you won’t manage people, you’ll be expected to lead technically, mentor teammates, and help set the standard for applied data science. This is a US‑remote role with regular collaboration across commercial teams.

What You’ll Be Doing

• Design, build, and iterate on predictive models for customer churn, retention, and expansion
• Develop early‑signal frameworks to estimate customer lifetime value well before traditional cohort analysis
• Build customer segmentation models that inform prioritization and targeting across go‑to‑market teams
• Partner closely with Customer Success, Account Management, and Marketing to translate ambiguous questions into modeling solutions
• Incorporate uplift and attribution concepts to connect customer actions and interactions to expected outcomes
• Validate model performance, monitor outcomes, and continuously improve prediction quality
• Collaborate with data engineering to support batch deployment and operationalization of models
• Mentor analysts and peers on modeling approaches, feature engineering, and best practices

What They’re Looking For

• 6+ years of experience in data science with ownership over impactful machine learning projects
• Strong experience building models for churn, retention, customer lifetime value, or segmentation
• Advanced proficiency in Python and SQL
• Demonstrated experience deploying machine learning models into production or operational workflows
• Solid understanding of B2B SaaS business models and sales cycles
• Ability to communicate complex model outputs clearly to non‑technical stakeholders
• Proven ability to operate independently, owning problems end‑to‑end in ambiguous environments

Nice to Have

• Exposure to analytical engineering or ML production architecture
• Experience working alongside data engineering teams on model deployment
• Familiarity with causal inference or marketing effectiveness modeling
• Comfort using modern developer tooling to accelerate modeling workflows

• Seniority Level

  Mid-Senior level

• Industry

  • Software Development
  • IT Services and IT Consulting

• Employment Type

  Full-time

• Job Functions

  • Engineering
  • Information Technology

• Skills

  • Data Science
  • Statistics
  • Machine Learning
  • Java
  • Software Development
  • Data Analytics
  • Data Analysis
  • Analytics
  • SQL
  • Algorithms
  • Python (Programming La

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Staff Data Scientist

Location: New York City (Hybrid)

Compensation: Up to $250,000 base + bonus + equity

Company Overview

A high-growth consumer fintech and e-commerce platform is building the credit infrastructure powering digital commerce in a large, underserved market. The business has reached profitability, processes hundreds of millions in annual transaction volume, and continues to scale rapidly with strong backing from top-tier investors.

The team is lean, highly technical, and composed of leaders from globally recognized technology and marketplace companies. This is an opportunity to join at a pivotal stage and directly influence core revenue-driving systems.

The Role

As a Staff Data Scientist, you will play a critical role in developing and deploying machine learning models that directly impact the company’s P&L. You’ll work across credit risk, pricing, and marketplace optimization problems, owning the full lifecycle from problem definition through to production.

This is a highly cross-functional role partnering with engineering, product, and leadership to drive data-informed decisions and scalable modeling solutions.

Key Responsibilities

• Build and deploy machine learning models for underwriting, credit risk, and portfolio optimization
• Develop pricing, ranking, and personalization algorithms to improve marketplace performance
• Apply causal inference and experimentation techniques to optimize decision-making
• Own projects end-to-end: from exploratory analysis and modeling through to production deployment
• Translate complex modeling outputs into clear business insights and recommendations
• Collaborate closely with engineering and product teams to operationalize models

Requirements

• 5+ years of experience in data science or machine learning in a production environment
• Strong foundation in statistical modeling and machine learning (e.g., classification, ensemble methods)
• Experience deploying models into production and iterating based on real-world performance
• Proficiency in Python and SQL
• Experience with experimentation, causal inference, or uplift modeling
• Strong problem-solving skills with the ability to operate in ambiguous, fast-paced environments

Preferred Background

• Advanced degree (PhD or Master’s) in a quantitative field such as Statistics, Mathematics, Economics, or Operations Research
• Experience in fintech, lending, or credit risk modeling
• Exposure to marketplace, pricing, or recommendation systems
• Familiarity with optimization techniques and constrained modeling problems

What Makes This Opportunity Unique

• Direct ownership of models that impact revenue and risk
• High visibility role working closely with senior leadership
• Fast-paced, startup environment with significant autonomy
• Opportunity to shape core data science strategy and systems

• If you’re excited by building high-impact machine learning systems in a fast-moving environment and want to see your work directly drive business outcomes, this is a unique opportunity to do so at scale.

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Senior Data Scientist

Manchester (2 days on site)

A high‑growth SaaS scale‑up is hiring a Senior Data Scientist to build their first production AI capabilities. You will work end to end across ideation, prototyping, and deployment, shaping how customers detect fraud, block invalid traffic, and optimise real‑time behavioural analytics.

The Company

They are a rapidly scaling SaaS business specialising in privacy‑compliant, cookieless analytics.

They process billions of data rows weekly to prevent wasteful and fraudulent traffic.

Their platform uniquely combines real‑time behaviour modelling, fraud detection, and optimisation.

The Role

* Deliver full lifecycle AI and ML projects from prototype to production.

* Build applied AI workflows including LLMs, NLP, and RAG‑based solutions.

* Work with large and messy tabular datasets to create high‑impact models.

* Develop classification and optimisation approaches to enhance customer outcomes.

* Partner with Product and Engineering to integrate models into the platform.

* Lead the transition toward a more AI‑driven product ecosystem.

Your Skills and Experience

* Strong commercial experience deploying AI and ML systems into production.

* Hands‑on experience with LLMs, NLP, or retrieval‑augmented workflows.

* Confident working with large‑scale tabular datasets and complex data environments.

* Cloud experience, ideally AWS, plus familiarity with MLOps practices.

* Background in product‑focused environments or consultancy.

* Ability to evidence measurable business impact from previous technical projects.

What They Offer

* Hybrid working with two office days weekly.

* High levels of ownership across AI strategy and delivery.

* Opportunity to build the company’s first production AI systems.

* Collaborative culture within a scaling SaaS environment.

* Clear progression as the AI function grows.

How to Apply

To register your interest, please apply with your CV.

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Senior Data Scientist

London Hybrid (2 days x week)

This is an opportunity to join a growing Data and AI business building production grade machine learning and LLM driven products for financial services and trading environments. The role offers exposure to both proprietary software and consultancy led problem solving, with real ownership over models that move into live use rather than staying at proof of concept stage.

The Company
They are a well established Data and AI organisation that has been operating successfully for several years, combining proprietary tooling with consultancy expertise. Their products support data driven decision making across financial services, including advanced analytical assistants and conversational AI solutions. The business is technically led, collaborative, and focused on building high quality, scalable machine learning systems.

The Role
You will work as part of a close knit data science team, contributing to the design, development and deployment of machine learning and LLM based solutions.
Responsibilities include:

• Designing and building machine learning models used by trading and financial services clients.
• Developing NLP and LLM powered chat engines that surface insights and factual answers from complex data.
• Fine tuning deep learning and large language models, including extraction and parameter optimisation.
• Working end to end on models that are taken through to production rather than remaining as prototypes.
• Contributing to products such as data assistance tools, website chatbots and analytical AI platforms.

Your Skills and Experience

• Hands on experience building and deploying machine learning models end to end.
• Experience with LLMs, NLP, conversational AI, RAG pipelines and model fine tuning.
• Understanding of production grade ML workflows and CI CD principles.
• Experience building chatbots or NLP driven chat engines used in live environments.
• Comfortable working independently and taking ownership of complex problems.

What They Offer

• Hybrid working with two days per week in a London office.
• Remote flexibility for candidates based in the North, with office visits around twice per month.
• The chance to work on impactful AI products used in real commercial and trading environments.
• A supportive team structure with senior mentorship and clear technical progression.

How to Apply
If you are a Senior Data Scientist looking to work on production level ML and LLM solutions within financial services, apply now to find out more.

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Data Scientist
London, 60,000 to 70,000 plus benefits, hybrid working, no sponsorship

This role offers the chance to step into a high‑impact data science position within a fast‑moving pricing environment where analytics directly influences commercial outcomes. You will work on complex, real‑world modelling problems with genuine ownership and visibility, rather than supporting work at the edges of the business.

The Company
They are a well‑established European insurance business operating in a highly data‑driven and technology‑led environment. With strong backing and ambitious growth plans in the UK, analytics plays a central role in how they compete and respond to market change. The culture is collaborative, fast paced and focused on building advanced analytical capability in‑house.

The Role

• Work within a pricing and underwriting data science team, building and improving predictive models that influence commercial strategy.
• Develop pricing and risk models that balance competitiveness with profitability.
• Explore, evaluate and integrate new data sources to enhance model performance.
• Use statistical thinking, logic and reasoning to simulate customer behaviour, including risk frequency and price sensitivity.
• Communicate insights clearly and influence decision‑making across technical and non‑technical stakeholders.
• Partner closely with machine learning engineers and other data professionals to deploy robust, scalable solutions.

Your Skills and Experience

• Strong commercial experience in data science or statistical modelling within any industry.
• Advanced Python skills for analysis and modelling.
• A solid grounding in statistical or mathematical concepts and applied problem solving.
• Confidence reasoning through complex problems and explaining your approach clearly.
• Experience working with end‑to‑end modelling problems, from concept through to impact.
• You must already have the right to work in the UK, as sponsorship is not available.

What They Offer

• Salary ranging from 60,000 to 75,000 depending on experience.
• Hybrid working with 1 to 2 days per week in the London office.
• High levels of autonomy and ownership over meaningful projects.
• Exposure to a wide range of analytical challenges in a fast‑growing business.
• Clear opportunities for progression as the UK data function continues to scale.

How to Apply
Apply now to learn more about this data science opportunity within a high‑impact pricing team.

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Data Scientist
London hybrid (1 to 2 days in the office) | £45,000 to £50,000 + benefits
Must have a masters in Maths or Physics from a Russell Group University
No sponsorship.

This is an opportunity to join a fast-growing insurance business at a pivotal stage of its UK expansion. You will sit in a highly analytical pricing and underwriting team, working on commercially critical models that directly influence pricing strategy, customer behaviour, and market competitiveness. The role offers strong ownership, rapid learning, and clear progression in a business that invests heavily in developing its data talent.

The Company

They are a European insurance provider operating in a highly competitive market, known for using data and technology as a core differentiator. Having achieved significant scale in their home market, they are now expanding rapidly across Europe with strong financial backing and ambitious growth plans. The culture is fast paced, highly data driven, and focused on building advanced analytical capability ahead of the market. They place particular emphasis on developing high-potential individuals and giving them exposure to meaningful, business-critical work.

The Role

• Work within the pricing and underwriting function to improve price accuracy and competitiveness
• Build and develop predictive models to better understand risk, customer behaviour, and pricing sensitivity
• Explore and integrate new data sources to enhance existing pricing and risk models
• Simulate customer behaviour, such as claim likelihood and response to pricing changes
• Translate analytical insights into practical recommendations that support new business growth
• Collaborate closely with other data scientists, machine learning engineers, and stakeholders across the business

Your Skills & Experience

• Strong academic background in a quantitative subject such as Mathematics or Physics
• Excellent logical reasoning and problem-solving ability
• Experience applying data science or modelling techniques in a commercial environment, or strong academic project experience
• Python experience is essential, with openness around other tools and technologies
• Ability to communicate complex ideas clearly and reason through problems out loud
• Motivated, curious, and keen to develop quickly in a demanding analytical environment

What They Offer

• Salary from £45,000 to £50,000 for strong Master’s graduates
• Hybrid working with 1 to 2 days per week in the London office
• Exposure to a wide range of pricing and modelling projects with real commercial impact
• Strong learning culture with support, mentorship, and clear development pathways
• Opportunity to join a growing UK analytics function within a well-funded, high-growth business

How to Apply

If you are interested in this Data Scientist role and want to find out more, please apply!

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Data Scientist
London, 45,000 to 50,000 plus benefits, hybrid working 1 to 2 days per week, No sponsorship available

This is a standout opportunity for a high‑potential graduate to launch a data science career in a business where analytics directly shapes commercial decisions. You will join a pricing team known for developing early‑career talent, offering real ownership, structured learning and exposure to impactful projects from day one.

The Company
They are a fast‑growing European motor insurance business operating in a highly data‑driven, technology‑led environment. Having successfully scaled across multiple markets, they are now investing heavily in their UK analytical capability. The culture is ambitious, collaborative and focused on hiring bright, curious people with strong problem‑solving ability.

The Role

• Work within a data science function aligned to pricing and underwriting.
• Build and improve predictive models to support pricing competitiveness and risk management.
• Use logical reasoning and statistical thinking to simulate customer behaviour, including risk and price sensitivity.
• Explore and assess new data sources to enhance modelling performance.
• Communicate your approach and reasoning clearly when solving complex problems.
• Collaborate closely with experienced data scientists and machine learning engineers.

Your Skills and Experience

• A Masters degree in Mathematics, Physics or a closely related quantitative subject.
• Strong academic performance with a 2.1 or above.
• Excellent logical, analytical and problem‑solving skills.
• Motivation, curiosity and a clear interest in applied data science.
• Ability to explain your thinking and approach when tackling unfamiliar problems.
• Any exposure to Python or analytical programming is beneficial but not essential for graduates.
• You must already have the right to work in the UK, as sponsorship is not available for this role.

What They Offer

• Salary of 45,000 to 50,000.
• Hybrid working with 1 to 2 days per week in the London office.
• Structured training, mentorship and clear development pathways within data science.
• High levels of responsibility and ownership early in your career.
• The chance to grow within a business that genuinely values data and invests in its people.

How to Apply
Apply now to learn more about this graduate data science opportunity within a high‑performing pricing team.

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Staff Data Scientist – Credit & Marketplace

Up to $280k base + significant equity

New York | In‑office (3-4 days/week)

We’re partnering with a Series A fintech building a credit‑led marketplace – a platform where data science sits at the heart of both credit decisioning and marketplace optimisation.

This is a rare opportunity to join at a stage where models are still being defined, not inherited. The team is hiring a Senior to Staff‑level Data Scientist to help shape the decision engine that determines who gets access to credit, how risk is priced, and how the marketplace allocates supply and demand.

They’re open to two backgrounds – but only at the very top end of the market:

• Credit / lending data scientists
• Elite marketplace data scientists (pricing, ranking, matching, experimentation)
• ✅ Successful Series A (o similar) experience is strongly preferred

Why This Role Is Different

Most DS roles optimise metrics. This one moves money. Your models will directly impact:

• Credit approval decisions
• Pricing and margin
• Portfolio performance and growth velocity

This is not a reporting or support role – it’s a core decision‑making seat for someone with a high grade ML / Data Science skillset.

What You’ll Do

• Design, build and iterate on credit underwriting and pricing models used in live production
• Tackle high‑stakes, constrained optimisation problems across credit and marketplace decisioning
• Apply causal and experimental thinking where clean A/B tests aren’t possible
• Own the full lifecycle: EDA → modelling → deployment, partnering closely with engineering
• Help define modelling standards, trade‑offs, and decision frameworks at an early stage

Who They’re Looking For

• Staff‑level Data Scientist
• Strong preference for successful Series A (or early Series B) experience
• Background in credit, lending, fintech, BNPL, or adjacent decisioning‑heavy domains like marketplace
• PhD or PhD‑level rigour strongly preferred (but not required if experience demonstrates depth)
• Strong Python & SQL; comfortable owning production‑facing logic
• Someone who thrives in ambiguity, speed, and ownership

Compensation & Logistics

• Base salary up to $280k (depending on level)
• Significant equity
• NYC based, 3-4 days in office
• No visa sponsorship
• If you’ve already helped scale a Series A company – and want to do it again with real ownership and influence – this is a rare opportunity.

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