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Principal Data Engineer (L5) / Staff Data Engineer

Remote – United States
Base Salary: $220,000 – $240,000
Eligibility: U.S. Citizen or Green Card holder required

Overview

A leading digital product and AI engineering firm is seeking a Principal Data Engineer (L5) to join a high-impact, multi-disciplinary team building modern, enterprise-grade data platforms.

This is a senior technical leadership role suited for an experienced engineer who can define data strategy, make end-to-end platform decisions, and influence engineering direction across complex engagements. You will operate at the intersection of data engineering and AI, helping deliver production-ready systems at speed while maintaining high standards in performance, reliability, and security.

Why This Role Matters

You will play a critical role in shaping how AI-powered data systems integrate into real-world enterprise workflows. The team operates at high velocity, delivering production-grade solutions in accelerated timelines, requiring strong ownership, technical craftsmanship, and the ability to execute with precision.

This role provides visibility across platform architecture, client impact, and internal engineering standards-ideal for someone who wants to influence both technical direction and team capability.

Key Responsibilities

Data Architecture & Platform Ownership

• Define and lead data architecture strategy across data lakes, warehouses, and pipelines
• Design scalable, high-performance systems for batch and real-time data processing
• Drive modernization efforts, optimizing for cost, performance, and scalability
• Establish data contracts and event-driven architectures across distributed systems
• Integrate data platforms with APIs, middleware, and third-party systems

AI & Advanced Data Systems

• Design and implement data pipelines supporting production AI/ML systems, including:
  • Embeddings and vector databases
  • Retrieval-Augmented Generation (RAG) data preparation
  • Feature stores and model training/inference pipelines
• Apply an AI-forward approach using modern development tools (e.g., Claude, Cursor)

Governance, Quality & Reliability

• Define and enforce data governance, quality standards, and compliance frameworks
• Implement monitoring, logging, and alerting systems across data pipelines
• Contribute to CI/CD pipelines for data workflows and automated deployment

Leadership & Collaboration

• Partner with leadership to shape data strategy and translate technical complexity into actionable decisions
• Mentor and guide junior and mid-level engineers, elevating team capability
• Establish engineering standards and best practices across data platforms
• Collaborate with engineering, product, analytics, and AI teams to align on execution

Required Qualifications

• 7+ years of experience in data engineering, including leadership of complex data platform initiatives
• 7+ years of hands-on experience with AWS, with recent, production-level usage required
• Strong background in distributed systems and large-scale data architecture
• Expertise in Python, Scala, and SQL
• Deep experience with cloud-native data platforms and enterprise data warehousing
• Strong knowledge of data pipeline orchestration and transformation frameworks
• Experience with streaming and real-time systems (Kafka, Kinesis, Pub/Sub, etc.)
• Proven expertise in data modeling and scalable data design
• Hands-on experience with governance, compliance, and data quality frameworks
• Experience with containerization and CI/CD for data systems
• Demonstrated experience building pipelines for AI/ML production systems
• Strong communication skills with the ability to influence cross-functional stakeholders
• Track record of mentoring engineers and leading technical decisions

Preferred / Nice-to-Have

• Experience with data mesh, data fabric, or lakehouse architectures
• Background in healthcare data systems
• AWS certifications (e.g., AWS Certified Data Engineer – Associate)

Interview Process

• 30-minute Culture Interview
• 30-45 minute Technical Interview
• Final Client Interview

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Lead Data Scientist

London – hybrid (1 day every 2 weeks)

The Company
They are a London-based technology organisation operating in the digital advertising and media space. Established in recent years, they have grown to around 50 employees and are continuing to scale their product and data capabilities. Their SaaS platform integrates with major advertising ecosystems and combines advanced machine learning with external datasets to optimise campaign outcomes. The business offers a collaborative, product-focused environment with strong technical ownership.

The Role

• Lead development of optimisation and predictive models for digital advertising campaigns
• Build and refine bidding algorithms within auction-based environments
• Take models from Python prototypes into production systems in AWS
• Work closely with engineering teams to deploy and scale solutions
• Utilise large-scale datasets from ad platforms and external sources
• Act as the go-to expert for improving and troubleshooting models
• Contribute to the ongoing evolution of data science capability across the platform

Your Skills and Experience

• Strong commercial experience building and deploying machine learning models
• Experience working on optimisation problems or performance-driven systems
• Understanding of auction-based modelling, pricing, or similar complex environments
• Proficiency in Python and exposure to production-level programming
• Familiarity with languages such as Kotlin, Java or Scala
• Experience working with large datasets, with exposure to tools such as PySpark beneficial
• Interest in working across both data science and production environments

What They Offer

• Flexible hybrid working with minimal office requirements in London
• Technical ownership in a senior individual contributor role
• Opportunity to work closely with engineering and influence product direction
• Collaborative environment with strong growth potential

How to Apply
If you would like to find out more, please apply with your CV or get in touch for an initial discussion.

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AI Automation Engineer
REMOTE | $150,000 – $200,000 + benefits

This is an opportunity to join a fast-growing, product-led organisation building AI-driven solutions to transform operational workflows at scale. You will play a key role in shaping how automation and AI are embedded across complex business processes, delivering measurable impact and driving efficiency across the organisation.

The Company
They are an innovative, technology-focused organisation operating at the intersection of software, automation, and operational services. With a strong emphasis on building scalable, AI-native platforms, they are focused on reducing manual workload and improving outcomes through intelligent systems. The business is growing rapidly and offers a collaborative, high-impact environment where engineers work closely with non-technical stakeholders to drive change.

The Role

• Identify high-impact automation opportunities by partnering directly with operational teams
• Design and build scalable backend services and workflow automations
• Develop AI-powered tools that streamline complex processes and decision-making
• Redesign existing workflows to improve efficiency rather than simply automating legacy processes
• Translate real-world business logic, including exceptions and edge cases, into robust systems
• Continuously iterate based on user feedback and performance metrics
• Contribute to defining best practices for AI-led automation across the business

Your Skills & Experience

• Strong commercial experience in backend, full-stack, or platform engineering
• Proven ability to design and implement workflow automation solutions in complex environments
• Experience working closely with non-technical stakeholders to uncover requirements
• Strong understanding of AI-driven development tools and automation frameworks
• Proficiency in modern programming languages such as TypeScript and working with relational databases
• Demonstrated ability to operate in fast-paced, ambiguous environments with high autonomy
• Strong product mindset with a focus on delivering measurable business impact

What They Offer

• Competitive salary of $150,000 – $200,000
• Comprehensive benefits package
• Opportunity to work on cutting-edge AI and automation challenges
• Clear progression in a rapidly scaling organisation
• Collaborative, high-ownership culture with exposure to senior stakeholders

How to Apply
If you are interested in applying for this AI Automation Engineer role, please submit your CV to be considered.

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Lead Data Scientist

This is an exciting opportunity to join a growing data-driven technology business shaping the future of digital advertising. With a strong foundation already in place, you will take ownership of advanced modelling initiatives and play a central role in scaling machine learning solutions into production.

The Role
You will act as the technical lead for data science, partnering closely with engineering to deliver production-ready models that drive measurable impact.

• Lead the development of optimisation and predictive models for digital advertising campaigns
• Design and refine bidding algorithms in auction-based environments
• Build prototypes in Python and support their transition into production systems using Kotlin within AWS
• Work with large-scale datasets from advertising platforms and external sources such as demographic and behavioural data
• Collaborate closely with data engineers to productionise machine learning solutions
• Act as the go-to expert for troubleshooting, improving, and scaling models
• Contribute to shaping the data science approach and best practices within the business

Your Skills and Experience

• Strong commercial experience in data science with a focus on predictive modelling and optimisation
• Proven ability to take models from concept through to production environments
• Advanced Python skills and experience with machine learning frameworks
• Understanding of working with large and complex datasets
• Experience or exposure to Kotlin, Java, or Scala, or a willingness to work with these technologies
• Familiarity with cloud environments and scalable data processing, such as PySpark
• Background in advertising technology, marketing analytics, or auction-based modelling is highly beneficial
• Interest in bridging data science with production and data engineering environments

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Principal Data Scientist – GenAI & Personalization – Remote (US) | $190k-$220k + 15% bonus

My client is a large, mission-driven learning technology organization reinventing itself as an AI‑first platform. Generative AI, personalization, and data science are now at the core of how millions of students learn – and they’re hiring a Principal Data Scientist to lead from the front.

This is a true hands-on principal IC role: deep technical ownership, real influence, no line management.

Why this role stands out

• Own and shape a core AI capability – scope built around your strengths
• Work on customer-facing GenAI products used at massive scale
• Strong leadership air cover – minimal meetings, protected focus time
• High-visibility work with real-world impact in education

What you’ll do

• Design and build GenAI systems that translate education standards into structured learning objectives
• Improve AI-driven assessments, content generation, and personalization engines
• Apply rigorous statistics to messy human data – and make it production-ready
• Partner closely with engineering on deployment, testing, and optimization

What they’re looking for

• PhD in Statistics or a highly quantitative field
• Strong generative AI experience (personalization or content generation a big plus)
• Excellent Python and end-to-end ownership – research → production → impact
• Clear communicator who can influence both technical and non-technical teams
• 4-5 years post-PhD industry experience

Bonus points for: MLOps, AWS/Databricks, or education experience (not required)

Logistics

• Fully remote (US-based)
• US Citizen or Green Card only (no sponsorship)
• Core availability: 11am-5pm EST

If you want principal-level ownership, meaningful scale, and the chance to define how GenAI shows up in real learning products – this role is built for that.

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Staff Data Scientist (GTM) | EU Remote

I’m partnering with a fast-growing B2B SaaS company on a high-impact Staff Data Scientist hire within their GTM Data function.

This is a rare role where you’re not just building models – you’re shaping how a business understands its customers. You’ll own the full lifecycle from problem framing through to production, and have a genuine seat at the table with senior leadership.

‘ :

* Building LTV and churn models that drive retention, upsell, and cross-sell strategy

* Developing predictive expansion models tied directly to revenue outcomes

* Bringing causal inference and Marketing Mix Modelling thinking to strategic marketing decisions

* Coaching analysts and embedding best practices across the team

‘ :

* 6+ years in applied data science

* Strong ML chops – churn, segmentation, LTV modeling

* B2B SaaS background (strongly preferred)

* Python + SQL as core tools

* At least one ML model shipped to production

* Someone who connects technical work to business outcomes – not just a list of tools on a CV

:

* Your experience is purely MMM or econometrics

* You’re heavily focused on LLMs/RAG

* You prefer a heavily structured environment with lots of oversight

UK Citizens and EU Citizens only.

If this sounds like your next move – or someone you know – drop me a message or comment below. Happy to share more details confidentially.

#DataScience #MachineLearning #SaaS #Hiring #DataJobs #LTV #ChurnModeling #RemoteJobs

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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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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, 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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