data & AI
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Data Scientist – Computer Vision & Object Detection

Location: Amsterdam

Type: Full-time

About Us

This company are a fast-growing, small and agile technology company building intelligent vision-based solutions that solve real-world problems. Our team moves quickly, takes ownership, and works collaboratively to turn ideas into production-ready products.

They are looking for a Data Scientist with strong Computer Vision expertise to join our team and take ownership of end-to-end object detection systems – from data collection and model development to deployment and optimisation in production.

The Role

As a Data Scientist (Computer Vision), you will be responsible for designing, building, and deploying object detection models in real-world environments. You will work across the full pipeline: data engineering, model training, evaluation, optimisation, and production integration.

This is a hands-on role in a small company, so you will have significant ownership and impact.

Key Responsibilities

• Develop, train, and optimise object detection models using Python and PyTorch
• Design and implement end-to-end computer vision pipelines
• Work with image/video datasets: collection, cleaning, annotation, augmentation
• Experiment with state-of-the-art detection architectures (e.g., YOLO, Faster R-CNN, Transformer-based models)
• Deploy models into production environments (edge, cloud, or hybrid)
• Optimise models for performance, latency, and scalability
• Collaborate closely with engineering and product teams
• Continuously research and evaluate new approaches in computer vision

Required Experience

• Strong experience in end-to-end computer vision systems
• Proven hands-on experience building and deploying object detection models
• Advanced proficiency in Python
• Strong experience with PyTorch
• Experience with model training, evaluation metrics (mAP, precision/recall, IoU)
• Experience handling real-world datasets (annotation tools, augmentation strategies)
• Understanding of model optimisation and performance tuning
• Experience deploying ML models to production

Nice to Have

• Experience with edge deployment (TensorRT, ONNX, quantisation)
• Familiarity with MLOps practices
• Experience with video analytics
• Experience working in a startup or small-company environment

What We’re Looking For

• Someone comfortable owning projects end-to-end
• A practical problem-solver who can ship working solutions
• Comfortable working in a small, fast-moving team
• Strong communication skills

What We Offer

• High ownership and impact
• Flexible working environment
• Opportunity to shape technical direction
• Competitive salary and equity options (if applicable)

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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 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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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

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior AI Engineer | Series C GRC Startup | San Francisco (Hybrid)

Location: San Francisco, CA (Hybrid – 3 days/week in office)

Compensation: $200,000 – $250,000 base salary + significant equity

The Role

This is a high-impact, high-ownership position. The selected candidate will serve as the technical authority on how the team designs, ships, and continuously improves AI in production. From LLM pipelines and RAG architectures to agentic workflows and human-in-the-loop systems, this engineer will work across the full stack of modern AI infrastructure alongside a team that takes engineering craft seriously.

What You’ll Do

• Design, build, and own production AI systems end-to-end, including LLM pipelines, retrieval-augmented generation (RAG), reranking, vector stores, and orchestration
• Architect scalable LLM + retrieval + agent systems that operate reliably in enterprise production environments
• Build and maintain human-in-the-loop (HITL) workflows that keep domain experts meaningfully in the decision process
• Develop evaluation frameworks and apply quantitative analysis to systematically measure and improve AI system performance
• Partner with product and engineering leadership to shape the AI roadmap and define best practices across the team
• Set architectural standards that influence how the broader organization builds and ships AI

Required:

• 10+ years of software engineering experience, including 3+ years working directly on ML/AI systems in production (or 6+ YOE for Senior level)
• Deep hands-on experience with RAG, embeddings, reranking, and vector databases (Pinecone, FAISS, Chroma, or similar)
• Proven experience building agentic workflows and multi-step LLM pipelines
• Strong proficiency in Python and TypeScript
• Experience designing and implementing AI evaluation frameworks using quantitative methods

Nice to Have:

• Background in compliance, security, or other regulated enterprise domains (GRC experience is a strong plus)
• Familiarity with enterprise data platforms or Snowflake-based analytics
• Experience with orchestration systems like Temporal or Airflow
• Hands-on experience with LLM evaluation platforms such as Braintrust

Compensation and Benefits

• $200,000 – $250,000 base salary + significant equity at Series C
• Employer-paid health, dental, and vision coverage for the employee and dependents
• 401(k) with company match
• Hybrid flexibility with a collaborative SF home base

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Analytics Engineer

Location: Costa Mesa, CA
Work Model: Hybrid (4 days onsite)
Compensation: $170,000 – $190,000 base + equity + benefits

About the Role

This role is for builders who think in systems – not dashboards.

You’ll define and own the core data layer that represents how the business actually operates. That means modeling real-world domains into structured, reusable systems that power decision-making, workflows, and internal applications across the company.

This is closer to data product engineering than traditional analytics. You’ll work across domains, partner directly with leadership, and turn messy operational reality into clean, scalable data models that others build on top of.

If you’ve ever wanted to move beyond reporting and build foundational systems that drive a company forward, this is that role.

Key Responsibilities

• Own and build domain-level data models that act as the source of truth across the business
• Design and maintain reusable, extensible data layers that scale across teams and use cases
• Build end-to-end data systems – ingestion, transformation, and serving layers
• Develop data products and internal applications, not just dashboards
• Partner with leadership and cross-functional teams to define how the business is measured and operated
• Drive data platform architecture and roadmap decisions
• Establish engineering best practices across testing, version control, and CI/CD for data
• Improve data reliability, governance, and accessibility at scale
• Identify and solve high-impact problems through better data modeling and system design

Must Haves

• 5+ years in Analytics Engineering, Data Engineering, or similar with strong engineering fundamentals
• Deep expertise in SQL and solid experience with Python (or similar)
• Proven track record building scalable, reusable data models used across an organization
• Hands-on ownership of data pipelines and transformation layers (dbt or equivalent)
• Experience with modern cloud data platforms (Snowflake, Redshift, BigQuery, etc.)
• Strong understanding of data modeling, schema design, and data quality systems
• Demonstrated end-to-end ownership of data systems in production environments
• Comfortable operating in fast-moving, ambiguous environments
• Strong communication skills with the ability to influence non-technical stakeholders
• Eligible to obtain and maintain a U.S. security clearance

Why Join

• Build core systems that define how the business runs, not just how it reports
• High ownership and autonomy – you will shape the data layer end-to-end
• Work on complex, high-stakes problems where data directly impacts real-world outcomes
• Join a team that values technical depth, speed, and systems thinking
• Opportunity to influence data platform architecture at scale
• Collaborate with highly capable engineers, operators, and product leaders
• Environment built for people who want to own, build, and move fast

To Apply for this Job Click Here

To Apply for this Job Click Here

DATA ENGINEER

up to £38,000 + benefits
Liverpool (Hybrid)
This is a great opportunity to join a purpose‑driven organisation where you can take ownership of data development and help modernise a traditional data estate as part of a growing Data & Insight function.

THE COMPANY:

This organisation is forward‑thinking and technology‑driven, with a strong focus on using data to improve people’s lives.
They are investing in a new data strategy and modern Microsoft stack, creating an excellent environment for someone early in their data career to grow and develop.

THE ROLE:

You will take ownership of SQL‑driven data development and reporting, supporting both BAU activity and longer‑term transformation projects. Working closely with the Data Engineering Manager, you’ll help deliver reliable data products for the wider business.
Key responsibilities include:

• Building and maintaining SQL‑based ETL pipelines across SSIS and Azure Data Factory
• Developing and delivering Power BI dashboards, datasets and data models
• Supporting and maintaining some existing SSRS reports
• Contributing to the ongoing modernisation of the data warehouse and presentation layer
• Supporting the transition toward Python, Azure and Microsoft Fabric

YOUR SKILLS AND EXPERIENCE:

You will bring strong capability in:

• SQL and ADF (Azure Data Factory)
• Power BI report development and data modelling
• Working with data warehouses and structured datasets
• Supporting ETL processes and data pipelines
• Communicating clearly with technical and non‑technical stakeholders

THE BENEFITS:

You will receive a salary of up to £38,000.

HOW TO APPLY:

Please register your interest by sending your CV to Molly Bird via the apply link on this page.

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