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Analytics Engineer
London, Hybrid (2 days in office) | Up to £85,000
No sponsorship available now or in the future.

This is an opportunity to join a high growth, product led business where data sits at the centre of decision making. You will play a key role in shaping scalable data models and powering insight across the organisation, directly influencing how products are built and improved.

The Company

They are a fast growing digital platform operating within the financial services space, supporting a large and expanding customer base across the UK. The business is mission driven, focused on helping people make smarter long term decisions, with data deeply embedded in their strategy. Their environment is collaborative, inclusive, and focused on continuous improvement, with strong investment in modern data tooling and practices.

The Role

As an Analytics Engineer, you will bridge the gap between data engineering and analytics by creating reliable, analysis ready datasets and scalable data models. You will work closely with analysts and stakeholders to enable high quality insights across the business.

• Design and build automated data transformations to create trusted datasets
• Develop and scale data models and data catalogues across the platform
• Collaborate with analysts and stakeholders to deliver new analytics features
• Improve code quality, documentation, and best practices across the team
• Champion analytics engineering principles within the wider data function
• Enable improved reporting and insight through well modelled data structures

Your Skills and Experience

• Strong commercial experience working with large datasets and delivering insight
• Advanced SQL skills within modern data platforms such as Snowflake, Databricks, or BigQuery
• Experience building and automating data pipelines and transformations
• Familiarity with dbt for data modelling and transformation workflows
• Working knowledge of Python for data processing
• Experience supporting BI tools such as Power BI or similar platforms
• Understanding of data warehouse modelling principles and best practices
• Experience with version control tools such as Git
• Exposure to CI/CD concepts is beneficial
• Experience within financial services is advantageous but not essential

What They Offer

• Salary up to £85,000
• Performance related bonus
• Hybrid working model with London office presence
• Company pension scheme
• Private medical insurance and health cash plan
• Annual learning and development budget
• Home office setup support
• Cycle to work and wellbeing benefits
• Generous annual leave with additional entitlement over time
• Inclusive and collaborative culture with clear progression opportunities

Please note that candidates must be based in the UK. Sponsorship is not available for this position.

How to Apply

If you are interested in applying your analytics engineering expertise in a growing, impact driven environment, please apply with your CV.

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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

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff Data Analyst – GTM

Location: Remote
Salary: $200-250k

This fast-growing, Series C cloud platform company is at the forefront of technological innovation, delivering cutting-edge solutions that drive industry transformation. The organization is seeking a highly skilled Staff Data Analyst to lead Go-to-Market (GTM) analytics efforts, enabling strategic growth and turning complex datasets into actionable insights to optimize GTM performance and operational efficiency.

About the Role

This position is central to defining and implementing data strategies that empower GTM teams. By developing metrics, automating reporting, and delivering insightful analyses, the Staff Data Analyst will play a critical role in optimizing growth strategies and ensuring data-driven decision-making.

Key Responsibilities

• Define and implement key GTM metrics to evaluate performance and uncover growth opportunities.
• Conduct in-depth analysis of complex datasets to deliver actionable GTM insights.
• Collaborate with cross-functional teams to identify root causes, refine processes, and inform strategic initiatives.
• Automate reporting workflows and create interactive dashboards to support leadership decision-making.
• Build and enhance datasets for growth optimization and cost reduction initiatives.
• Develop data accessibility solutions, ensuring timely and structured access to insights for all stakeholders.
• Shape the GTM analytics roadmap, aligning data projects with broader organizational goals.

About You

• 6+ years in analytics roles, with expertise in SaaS and product-led growth (PLG) business models.
• Advanced proficiency in SQL and experience with tools such as Looker, Hashboard, or Omni. Familiarity with Python or R and statistical modeling.
• Demonstrated ability to interpret trends, conduct root cause analysis, and deliver data-driven recommendations that influence strategy.
• Strong ability to present complex findings clearly to both technical and non-technical audiences.
• Proven success working in fast-paced, cross-functional environments to drive high-impact outcomes.

This is a unique opportunity to join a dynamic, data-driven organization and make a significant impact on the success of its GTM strategy. If you’re passionate about using data to drive innovation and thrive in a high-growth environment, this role is for you!

To Apply for this Job Click Here

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Lead AI Engineer
Location: San Francisco Bay Area | Hybrid
Salary: $250-300k + Equity

Join a well-funded, AI-native startup at the forefront of redefining how digital products are designed and shipped.

This team is building a next-generation design platform where every screen is real, production-ready code. Designers work directly in the medium that ships, not static mockups, with AI deeply embedded into the workflow to accelerate iteration while preserving precision, consistency, and control.

Backed by top-tier Bay Area investors and senior product leaders from companies including Shopify, Notion, Dropbox, Stripe, and OpenAI, the company has strong runway, a high bar for talent, and ambitious plans ahead.

They’re now hiring their first dedicated Lead AI Engineer to own the model layer and drive AI performance across the product.

The Opportunity

You’ll work directly with the CTO and founding team to define and execute the AI strategy at the model level.

This is a hands-on, production-focused AI engineering role centered on:

• Fine-tuning LLMs for real-world use cases
• Optimizing inference speed, cost, and reliability
• Designing and deploying custom Small Language Models (SLMs)
• Establishing evaluation, benchmarking, and observability standards

What You’ll Be Responsible For

Fine-Tuning & Model Strategy

• Own fine-tuning workflows (LoRA, adapters, distillation, full fine-tuning)
• Decide when to fine-tune vs optimize at the system or prompt level
• Iterate models based on production feedback
• Balance quality, latency, and cost tradeoffs

Model Optimization & Performance

• Improve inference speed and throughput
• Reduce cost per request
• Enhance reliability and output consistency
• Define model evaluation and benchmarking frameworks

Custom SLM Development

• Design and train custom SLMs for specific design-to-code workflows
• Identify when smaller models outperform larger ones
• Deploy and maintain real-time, streaming AI systems
• Support multi-step and agentic AI capabilities within the product

What They’re Looking For

• 5+ years of software engineering experience
• 2+ years building with LLMs in production environments
• Proven hands-on fine-tuning experience (LoRA, distillation, adapters, etc.)
• Experience deploying custom or specialized models
• Strong intuition around inference tradeoffs: latency, throughput, cost, reliability
• Proficiency in Python and TypeScript / Node.js

Nice to have:

• ONNX runtime or model optimization tooling
• Experience with orchestration frameworks (e.g., LangChain)
• WebSockets, Redis, or real-time streaming systems
• Background in AI-native or code-generation products
• A PhD or advanced degree is welcomed, but demonstrated production impact is the priority.

To Apply for this Job Click Here

To Apply for this Job Click Here

AI Software Engineer

Remote (US – ET/CT Time Zone)
$120K-$160K + Benefits

I’m partnering with a global leader in digital learning technology that’s transforming how millions of students and educators experience personalized, AI-powered learning. Following major investment in generative AI, the company is scaling its AI Platform Engineering team to build the next generation of adaptive learning tools.

This is a hands-on engineering role focused on building production-grade generative AI applications that power multiple products across the business.

The Role:

You’ll design and build scalable, full-stack systems that integrate large language models and AI capabilities into digital learning platforms. Working closely with data scientists, product managers, and engineers, you’ll help take GenAI prototypes from experimentation to production-driving forward real-world AI impact.

Key Responsibilities

• Develop and maintain AI-powered applications and platform services that are reliable, scalable, and secure
• Build and optimize LLM-based and RAG-powered solutions using frameworks such as LangChain or LangGraph
• Collaborate with Data Science teams to productionize models and streamline deployment pipelines
• Lead and contribute to technical design, architecture, and CI/CD improvements
• Ensure applications meet accessibility (WCAG 2.2 AA), performance, and security standards
• Stay current on the latest advancements in GenAI and advocate for best practices across the team

About You

• 5+ years of professional software engineering experience
• Strong full-stack skills across:
• Backend: Python, Node.js, or Go
• Frontend: Angular or React
• Databases: MySQL/PostgreSQL + NoSQL (e.g., DynamoDB)
• Cloud/Infra: AWS or Azure, Terraform, CI/CD tools
• Hands-on experience building AI/GenAI-enabled applications (Azure OpenAI, Amazon Bedrock, etc.)
• Practical understanding of RAG techniques, vector databases, and AI orchestration tools
• Strong system design, performance optimization, and collaboration skills
• Passionate about building impactful technology and staying ahead in the AI space

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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

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Engineer

San Francisco, CA

$180-240K base + equity

We’re partnered with one of the most recognized developer platforms in the world, trusted by engineering teams at OpenAI, Meta, Netflix, and Adobe, who are scaling their data platform and looking to hire a Senior Data Engineer to own the pipelines and foundations at the core of their data ecosystem.

You’ll own the full pipeline lifecycle, from ingestion architecture through to analytics-ready data, working closely with Data Platform Engineers and partnering with analysts and data scientists who depend on what you build every day.

What you’ll do

• Design and build scalable ingestion pipelines and orchestration frameworks across structured, semi-structured, and event-based sources
• Own reliability, observability, and performance across the full pipeline lifecycle from raw ingestion to analytics-ready delivery
• Build and maintain dbt transformation pipelines serving as the single source of truth across Finance, Product, GTM, and Engineering
• Ensure revenue and billing data meets the accuracy and auditability required for public company reporting, including SOX compliance
• Apply software engineering principles throughout: CI/CD, testing, observability, version control, and automation
• Enable self-serve analytics through semantic layer development, strong abstractions, and clear documentation
• Champion data quality and governance across classification, ownership, access policies, and data lifecycle management

What we’re looking for

• 5+ years in data engineering or a hybrid data/analytics engineering role, with a track record of owning pipelines end-to-end in high-growth or enterprise environments
• Advanced SQL and dbt (Core or Cloud), Snowflake or comparable cloud data warehouse, Python, and Airflow
• Experience with Kafka and streaming data systems, with working knowledge of ClickHouse, Iceberg, or similar technologies
• Experience with ingestion tools such as Fivetran, Airbyte, or Polytomic
• Cloud-native architecture experience across AWS, GCP, or Azure
• Exposure to designing data systems that meet compliance and governance requirements, including SOX or equivalent
• Strong communication and collaboration skills, with the ability to contribute as a technical voice across engineering and business stakeholders

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Analyst

Remote (US Based)

$150-170k base salary

A mission driven SaaS company supporting thousands of nonprofit organizations is expanding its data and analytics capability. The platform powers donor management, fundraising, and payments, helping nonprofits strengthen communities and drive real impact. As the business scales, data is becoming central to decision making across the organization.

The Role:

This Senior Data Analyst role offers true end to end ownership of analytics. You will work across data modeling, analytics engineering, reporting, and stakeholder enablement, with a clear focus on moving the business from reactive reporting to forward looking, insight driven analysis.

You will be embedded within the Finance organization and partner closely with leaders across Finance, Sales, GTM, RevOps, and Product. This is a senior individual contributor role with scope to grow into people leadership as the data function matures.

What you will do:

• Own the analytics stack end to end, from data modeling in Snowflake to dashboards in Metabase
• Build and maintain high quality data models that support trusted reporting and analysis
• Lead the move away from legacy BI tools and establish a single source of truth
• Deliver self service dashboards for Finance, GTM, RevOps, and Product teams
• Partner with stakeholders to translate business questions into scalable analytics solutions
• Proactively surface insights that influence strategy and decision making
• Improve data quality, consistency, and usability across the analytics layer
• Help shape analytics standards, tooling, and best practices
• Support the evolution toward predictive and forward looking analytics

What we are looking for:

• Five to seven plus years of experience in analytics, data analysis, or analytics engineering
• Strong SQL skills with hands on Snowflake experience
• Experience building dashboards in Metabase
• Proven strength in data modeling and owning analytics foundations end to end
• Experience working cross functionally with Finance, Sales, GTM, RevOps, and Product
• Ability to operate independently and take full ownership of analytics domains
• Experience with dbt, experimentation, forecasting, or predictive analytics is a plus
• Interest in AI enabled analytics and modern data tooling
• Strong communication skills with non technical stakeholders

This role is ideal for a senior analyst who wants ownership, visibility, and the opportunity to shape how data is used across a growing SaaS organization with a strong social mission.

To Apply for this Job Click Here

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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

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff Data Engineer

San Francisco, CA

$240K-$300K base + equity

We’re partnered with one of the most recognized developer platforms in the world, trusted by engineering teams at OpenAI, Meta, Netflix, and Adobe, who are scaling their data platform and looking to hire a Senior Data Engineer to own the pipelines and foundations at the core of their data ecosystem.

You’ll own the full pipeline lifecycle, from ingestion architecture through to analytics-ready data, working closely with Data Platform Engineers and partnering with analysts and data scientists who depend on what you build every day.

What You’ll Do

• Design and build scalable ingestion pipelines and orchestration frameworks across structured, semi-structured, and event-based sources
• Own reliability, observability, and performance across the full pipeline lifecycle from raw ingestion to analytics-ready delivery
• Build and maintain dbt transformation pipelines serving as the single source of truth across Finance, Product, GTM, and Engineering
• Ensure revenue and billing data meets the accuracy and auditability required for public company reporting, including SOX compliance
• Apply software engineering principles throughout: CI/CD, testing, observability, version control, and automation
• Enable self-serve analytics through semantic layer development, strong abstractions, and clear documentation
• Champion data quality and governance across classification, ownership, access policies, and data lifecycle management

What We’re Looking For

• 8+ years in data engineering or a hybrid data/analytics engineering role, with a track record of owning pipelines end-to-end in high-growth or enterprise environments
• Advanced SQL and dbt (Core or Cloud), Snowflake or comparable cloud data warehouse, Python, and Airflow
• Deep experience with Kafka and streaming data systems, with strong working knowledge of ClickHouse, Iceberg, or similar technologies
• Experience with ingestion tools such as Fivetran, Airbyte, or Polytomic
• Cloud-native architecture expertise across AWS, GCP, or Azure
• Experience designing and scaling data systems to support petabyte-level workloads
• Track record of building data infrastructure that meets compliance and governance requirements, including SOX or equivalent
• Strong communication and collaboration skills, with the ability to operate as a senior technical voice across engineering and business stakeholders

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Analytics Engineer

Location: Remote

Salary: $150-170k base

We’re partnering exclusively with a fast-growing SaaS company to find a Senior Analytics Engineer to join their data team. This is a high-impact, high-autonomy role sitting at the intersection of data engineering and analytics, perfect for someone who takes pride in building data foundations that the whole business relies on.

What You’ll Be Doing

• Designing and building dimensional data models in Snowflake that underpin analytics across the business
• Developing and optimising dbt models to turn raw source data into clean, trusted datasets
• Partnering with analysts and business stakeholders to translate their needs into scalable data solutions
• Implementing data quality checks and owning the reliability of analytics datasets
• Contributing to data governance including PII handling, metadata management, and documentation
• Supporting strategic analytics across customer journeys, revenue metrics, and product usage
• Mentoring junior team members and championing best practices

What We’re Looking For

The company runs a best-in-class modern data stack built around Snowflake, dbt, and Monte Carlo, with data flowing in from Salesforce, HubSpot, Recurly, and core product databases. The team is evolving toward an AI-enabled, domain-oriented data organisation, so there’s real scope to shape the architecture, not just maintain it.

Essential:

• 5+ years in analytics engineering, data engineering, or a similar data-focused role
• Expert-level SQL: complex queries, CTEs, window functions
• Strong hands-on dbt experience
• Snowflake (or equivalent cloud warehouse: BigQuery, Redshift)
• Solid understanding of dimensional modelling and data warehouse design patterns
• Experience with SaaS metrics: MRR, churn, CLV etc.
• Python for data work or automation
• Familiarity with data orchestration tools (Airflow / MWAA)
• Comfortable working remotely and cross-functionally with distributed teams

Nice to have:

• Experience with reverse ETL tools such as Hightouch
• Exposure to BI tools (Hex preferred)
• Understanding of data mesh or domain-oriented architecture concepts

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