About the role

Culture Amp is building toward a future where leaders and managers get meaningful, connected insights about their workforce: how engagement relates to performance, retention, team structure, and the other forces that shape how people experience work. We're early in this journey, and this role will help shape what that looks like.

You'll join our Data Products team, working alongside data scientists, engineers, and analysts who collectively own our benchmark pipelines, data enrichment, and the insights we surface to customers. Your focus will be on two things: making our workforce data richer and more reliable (standardising hierarchy data, tenure, demographics), and discovering insights that are genuinely useful to the leaders and managers who use our platform.

This isn't a role where you'll be handed a well-defined model to optimise. You'll be doing exploratory work to find patterns that matter, building and validating models, and working with engineers to productionise what you find. Some of your work will ship through Coach, our AI assistant, so you'll be directly influencing what insights our customers see and act on.

You'll also help maintain and improve our engagement survey benchmarks (one of the largest datasets of its kind), though most of your time will be on newer, less charted territory.

You'll work closely with the rest of the data science team, as well as engineers who can help take your work into production.

What you'll do

• Lead discovery work to find meaningful patterns in workforce data: what predicts engagement, retention, and performance outcomes?
• Build and validate statistical models and ML approaches to surface actionable insights
• Improve data quality and standardisation for workforce attributes like hierarchy, tenure, and demographics
• Partner with engineers to productionise insights, including integration with Coach
• Contribute to our engagement benchmarks: methodology improvements, new cuts, data quality
• Help shape the longer-term insights roadmap based on what you learn

What we're looking for

• Around 4–6 years of experience in data science or a related quantitative role
• Strong foundation in statistics and classical ML, with the judgment to pick the right tool for the problem
• Solid data modelling instincts: you understand how to structure and clean messy workforce data
• Expertise in Python and SQL with a focus on writing clean, reusable code to deliver end-to-end data science solutions.
• Experience taking models from exploration to production, even if you had help from engineers
• Clear thinking and communication: you can explain what you found and why it matters to product and business stakeholders
• You can present data in an interactive way that surfaces insights and conveys meaning to non-technical stakeholders. An interest or knack for data visualisation would be a bonus.
• Curiosity about the "so what": you care whether the correlations you find are actually useful
• Bonus points if you have experience with HR/people analytics data, causal inference, working with LLMs (RAG, prompting, evaluation), or building insights products.