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Director of Data
London | £120,000 to £140,000

This is a rare opportunity to step into a senior, visible data leadership role at a pivotal moment. The organisation has already invested heavily in its data foundations and products. Now they need a commercially minded Director of Data to maximise value, embed insight across the business, and turn data into a true growth driver.

The Company
They are a global marketing and rewards organisation working with major consumer brands to help them better understand, engage, and retain their customers. Operating internationally and backed by private equity, they are on a fast paced growth journey with a clear roadmap for their data capability. Data already underpins their products and client offering, and leadership is committed to evolving this into a more advanced, insight led and predictive proposition.

The Role
You will take ownership of an established data function and focus on execution rather than strategy creation. This role blends leadership, stakeholder engagement, and hands on analytical direction.
Key responsibilities include:

• Leading and developing a small, high calibre data team across analytics and engineering.
• Driving adoption of data and insight across the business, improving data literacy and decision making.
• Maximising the value of existing data products and platforms, identifying where deeper insight and advanced analytics can unlock commercial impact.
• Delivering predictive and advanced analytics use cases that support campaign optimisation, customer understanding, and product performance.
• Acting as a senior data voice with stakeholders, confidently presenting insight and influencing at leadership and board level.
• Partnering closely with product, technology, and commercial teams to ensure analytics is embedded into day to day operations.
• Contributing to the evolution of AI and advanced analytics capabilities, with a pragmatic and commercially focused approach.

Your Skills & Experience
To succeed in this role, you will bring:

• Strong experience leading analytics or insight functions within a commercial environment.
• Proven ability to translate data into clear, actionable insight for senior stakeholders.
• Hands on experience with advanced analytics, predictive modelling, or applied data science, without needing to be a deep specialist modeller.
• Solid technical understanding across SQL and Python, and modern data platforms such as Snowflake and product analytics tools.
• Experience executing against an existing data strategy and delivering measurable outcomes at pace.
• Confidence working in lean teams and remaining close to the detail, rather than managing large functions.
• Exposure to global data environments or international stakeholders.
• Experience within loyalty, consultancy, agency, or marketing led organisations is highly beneficial.
• Familiarity with AI or generative AI concepts, such as RAG systems or vector databases, and where these approaches add real business value.

What They Offer

• Salary between £120,000 and £140,000.
• London based role with an office first culture and some flexibility, ideally up to one day per week working from home.
• A highly visible leadership position with genuine influence on commercial outcomes.
• The chance to shape how data and advanced analytics are used across a global business.
• A collaborative, fast moving environment backed by committed senior leadership.

How to Apply
If you are a hands on data leader who enjoys turning insight into impact and leading from the front, please apply with your CV or get in touch to discuss the role in more detail.

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Lead Data Scientist

$175,000- $200,000

Pittsburgh, PA (Onsite)

THE ORGANISATION

A discreet, high‑growth technology group is expanding its advanced analytics and AI leadership capabilities. The organisation operates in a deeply complex environment where modelling, optimisation, and intelligent decision systems play a central role. They are investing heavily in next‑generation platforms that blend predictive modelling, simulation, and large‑scale automation to influence critical strategic choices.

THE ROLE

This is a senior technical and leadership role responsible for architecting sophisticated simulation, optimisation, and decision‑intelligence systems. You will guide the vision, design, and delivery of large‑scale AI solutions, combining hands‑on expertise with strategic leadership.

Your remit spans the development of system‑level simulations, optimisation engines, and complex modelling frameworks that support high‑impact decision workflows. You will define long‑range technical direction, lead major AI initiatives end‑to‑end, and mentor a highly skilled team of Data Scientists and AI Engineers.

This is a position for someone who thrives in ambiguity, enjoys solving multi‑variable, system‑level challenges, and brings strong conceptual and practical knowledge of advanced modelling.

KEY RESPONSIBILITIES

• Lead the architecture, design, and deployment of advanced simulation and optimisation platforms
• Build multi‑modal modelling systems incorporating predictive analytics, stochastic simulation, and strategic optimisation workflows
• Define the long‑term technical roadmap for modelling and decision‑intelligence initiatives
• Oversee large‑scale AI projects from initial scoping through to production launch
• Act as the senior technical authority on simulation, optimisation, and model strategy
• Develop scalable frameworks that support complex capability modelling and scenario analysis
• Lead the development of platform components that integrate simulation, optimisation, predictive modelling, and decision logic
• Mentor senior technical team members, raising the standard across modelling, experimentation, and delivery
• Establish modelling best practices, evaluation standards, and robust experimentation workflows
• Partner with cross‑functional teams to convert abstract, open‑ended challenges into concrete technical solutions
• Bring emerging research and methodologies (simulation techniques, optimisation methods, advanced model reasoning, etc.) into production systems
• Communicate modelling strategy, risk, and value clearly to both technical and non‑technical stakeholders

WHAT YOU BRING

• 7+ years of applied Data Science or similar experience in complex modelling domains
• Deep experience with simulation methodologies (e.g. discrete‑event, agent‑based, Monte‑Carlo, or similar approaches)
• Strong understanding of stochastic optimisation, Bayesian optimisation, and advanced mathematical modelling techniques
• Ability to design, evaluate, and scale large‑scale modelling systems and optimisation pipelines
• Strong Python engineering foundations and experience delivering production‑ready AI/ML systems
• Experience leading full lifecycle AI/DS projects, from ideation to deployment
• Proven track record of working with large datasets, complex modelling environments, and multi‑component systems
• Ability to mentor senior‑level technical staff and influence high‑level decision‑making
• Comfortable operating in a high‑autonomy, high‑ownership environment

DESIRABLE EXPERIENCE

• Experience with causal modelling, decision science, or structural modelling frameworks
• Experience with complex system evaluation, simulation benchmarking, or modelling validation
• Background in scaling AI/ML or optimisation systems across cloud environments
• Experience converting experimental prototypes into robust, enterprise‑ready solutions
• Strong publication or research contributions in modelling, optimisation, or related fields

THE OFFER

• Competitive Base Salary
• Opportunity to architect foundational modelling and optimisation systems for a major technology programme
• Significant autonomy and technical ownership
• Ability to shape modelling strategy, culture, and long‑term system design
• Work within a deeply technical team solving highly complex, meaningful challenges

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Lead AI Engineer

$200,000

Location: Pittsburgh, PA (Onsite)

THE COMPANY

A high‑growth, mission‑driven technology organisation is expanding its advanced AI function. The team specialises in building intelligent autonomous systems designed to operate across complex workflows and high‑stakes environments. Engineers here work on cutting‑edge agentic technologies with significant ownership and impact.

THE ROLE

As the Lead AI Engineer, you’ll guide a specialised engineering team responsible for designing, building, and deploying next‑generation agentic AI systems. You will lead technical strategy, architecture decisions, and hands‑on development, while also mentoring engineers and driving best‑in‑class standards for performance, reliability, and scalability.

You’ll oversee the development of agents capable of long‑horizon planning, tool‑use, memory, and coordination across multi‑agent environments, ensuring they can operate effectively in real‑world mission‑critical settings.

KEY RESPONSIBILITIES

• Lead the design and development of agentic AI systems from conception through production
• Architect multi‑agent systems with planning, routing, memory, and complex tool‑use
• Build modular “skills” and components that plug into backend systems and data pipelines
• Establish evaluation frameworks, telemetry systems, and observability tools for agent behaviour
• Guide Agile processes, technical planning, and day‑to‑day engineering execution
• Partner with product and delivery teams to solve complex operational challenges
• Provide mentorship and technical leadership to engineers and data scientists

EXPERIENCE REQUIRED

• Several years of experience building and deploying ML or LLM‑powered systems in production
• Experience leading or mentoring engineering teams
• Demonstrated expertise in LLM integration and agentic system development
• Strong Python engineering skills
• Hands‑on experience with cloud infrastructure (AWS preferred)
• Familiarity with LLM algorithms, scaling patterns, and system reliability
• Ability to operate autonomously in high‑pace, ambiguous environments
• Comfortable with Git and modern engineering workflows

DESIRABLE EXPERIENCE

• Experience designing or deploying complex multi‑agent architectures
• Exposure to startup or high‑growth engineering cultures
• Experience with GenAI coding tools or best practices for agentic systems
• Eligibility to work in secure or sensitive environments

THE OFFER

• Ownership over next‑generation agentic AI strategy and architecture
• Opportunity to lead a high‑impact engineering team
• Work with cutting‑edge LLM and agentic technologies
• Fast‑paced environment with strong technical autonomy

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Data Scientist (LLM)

Location: Chicago

Salary: Up to $170,000 + Benefits

An exciting opportunity has arisen for a Data Scientist to join a global SaaS organization that is transforming decision-making across a critical sector. With thousands of clients worldwide, this company is dedicated to delivering innovative solutions that drive measurable impact and operational efficiency.

The Role

The successful candidate will join a high-performing Analytics & Insights team, responsible for building predictive models and intelligent data pipelines that enable data-driven strategies. This position plays a key role in shaping product development and improving customer outcomes.

Key Responsibilities:

• Develop advanced statistical models and machine learning algorithms for predictive analytics and forecasting.
• Extract, clean, and transform complex datasets using SQL, Python, and modern ETL frameworks.
• Design and implement experiments to validate product impact and optimize outcomes.
• Collaborate with engineers, product managers, and domain experts to translate business challenges into data solutions.
• Implement monitoring and validation tools to ensure data quality and reliability.

What They’re Looking For

• Mid-level experience in data science or machine learning, ideally within SaaS or a data-driven industry.
• Proven track record of building and deploying end-to-end data solutions.
• Strong knowledge of statistical analysis, regression, time-series forecasting, clustering, and experimental design.
• Hands-on experience with SQL, Python (or R), and distributed data technologies (e.g., Spark, Hadoop, Kafka, or cloud platforms like AWS/GCP/Azure).
• Ability to troubleshoot and maintain scalable data workflows.
• A collaborative mindset and passion for using data to drive impact.

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Lead Data Scientist

$175,000 to $200,000

Location: Pittsburgh, PA (Onsite)

THE ORGANISATION

A quietly scaling technology group is investing heavily in next‑generation AI capabilities. Their work centres on high‑complexity data environments, advanced analytics, and intelligent systems that surface insight, support decision‑making, and power exploratory research. The culture values depth of thinking, technical rigour, and leaders who thrive in ambiguous, evolving problem spaces.

THE OPPORTUNITY

This position will lead the development of sophisticated search, retrieval, and reasoning systems built on large‑scale datasets and advanced modelling techniques. You will act as the senior technical authority architecting platforms, shaping long‑term strategy, and mentoring a high‑calibre team across both Data Science and AI Engineering.

The role blends deep research, hands‑on modelling, system design, and leadership. Expect to define the roadmap for how information is indexed, retrieved, ranked, explored, and transformed into actionable outcomes. This is a position for someone who enjoys building from first principles, driving technical direction, and delivering complex AI capabilities end‑to‑end.

WHAT YOU’LL LEAD

• Designing and building advanced retrieval, ranking, and AI‑driven research systems
• Setting the technical strategy and multi‑year roadmap for search, knowledge exploration, and agentic reasoning capabilities
• Architecting large‑scale pipelines combining embeddings, traditional search methods, knowledge graphs, and hybrid retrieval techniques
• Developing conversational exploration tools, structured reasoning systems, and intelligent query‑understanding models
• Acting as the principal technical contributor on high‑impact projects, while also coaching and elevating senior engineers and scientists
• Collaborating with product and engineering to translate open‑ended problem statements into clear, scalable technical plans
• Establishing best practices across experimentation, modelling, evaluation, and model lifecycle management
• Bringing cutting‑edge research (LLMs, retrieval, agentic behaviours, multimodal embeddings, etc.) into production environments
• Leading workshops, technical discussions, and internal knowledge‑building initiatives

WHAT YOU BRING

• 7+ years’ experience in applied Data Science or AI research within a production‑focused environment
• Background in search/retrieval, ranking systems, embeddings, or related areas
• Expertise in building and scaling RAG pipelines, hybrid retrieval architectures, or advanced indexing strategies
• Strong ability to design and evaluate multimodal embedding models, vector‑based retrieval, and graph‑driven systems
• Deep experience with ranking and reranking architectures (bi‑encoders, cross‑encoders, multi‑tower structures)
• Strong Python engineering fundamentals and experience deploying complex AI systems
• Experience with reasoning frameworks, orchestration approaches, or agentic system design
• Ability to guide high‑impact initiatives from ideation through to production release
• Strong communication skills and the ability to influence technical and non‑technical stakeholders

NICE TO HAVE

• Research publications or recognised contributions to AI/ML/NLP communities
• Experience in fine‑tuning or post‑training large models
• Familiarity with evaluation methods for complex retrieval and agentic systems
• Experience working with large‑scale cloud environments and MLOps frameworks
• Proven ability to transition research prototypes into stable, enterprise‑grade products

THE OFFER

• Competitive compensation
• Ownership of a foundational AI capability within a rapidly scaling technical environment
• Autonomy to shape long‑term direction, architecture, and technical standards
• Opportunity to work on complex, meaningful challenges with a highly skilled AI team

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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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