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Senior People Science Analyst (12 month FTC)

cultureamp

Berlin · senior

Job at a glance

Berlin
Location
Senior
Seniority
cultureamp
Employer

We’re big believers in the power of IRL, so for most roles we ask Campers to work from their local Culture Amp office an average of 2 days a week to unlock connection, pace and culture together. Join us on our mission to make a better world of work.  Culture Amp is the world’s leading employee experience platform, revolutionizing how 25 million employees across more than 6,000 companies create a better world of work.

Culture Amp empowers companies of all sizes and industries to transform employee engagement, drive performance management, and develop high-performing teams. Powered by people science and the most comprehensive employee dataset in the world, the most innovative companies including Canva, On, Asana, Dolby, McDonalds and Nasdaq depend on Culture Amp every day. Culture Amp is backed by leading venture capital funds and has offices in the US, UK, Germany and Australia.

Culture Amp has been recognized as one of the world’s top private cloud companies by Forbes and most innovative companies by Fast Company. For more information visit cultureamp.com . We're looking for a Senior People Science Analyst to join our global People Science Analytics team on a 12-month fixed term contract. You'll specifically partner with customers across EMEA and North America on bespoke research using Culture Amp and customer-supplied data, owning studies from question through to action.

GenAI tools will be part of that workflow, helping you work more efficiently, as you continue to identify further areas for improvement. As a thought leader in HR analytics, you'll combine data across diverse customers and use methods from psychology, economics and business to generate advanced insights into how employee experience shapes outcomes like turnover, sales performance and customer satisfaction.

You'll surface trends for the HR community and make complex findings accessible through clear, engaging stories and practical strategies. The work is technical and customer-facing. You'll listen closely to customers, bring clarity to methodology and reporting, and collaborate with HR leaders, customer-facing People Scientists, Customer Success Managers and Account Managers to develop studies and insight reports for clients and the wider public.

You'll also help customers and colleagues build confidence with data. Because the team is small and the projects are complex, you'll have real ownership over which questions are worth answering and how they get answered. As part of this team of amazing humans, You will: Lead customer discovery and own studies end to end, from clarifying the business problem and shaping the research question through to design, delivery and recommendations Design, clean, combine and explore platform and customer-supplied datasets using robust, reusable approaches that protect participant privacy Conduct rigorous statistical analyses across engagement, lifecycle, performance and team effectiveness data, generating actionable and, where appropriate, predictive insights tied to business outcomes Use AI tools to accelerate research, analysis, synthesis and communication, while validating outputs, protecting customer data and maintaining methodological rigour Collaborate with customer-facing People Scientists on advanced HR analytics projects, applying sound judgment about methods, limitations and trade-offs Identify the themes and stories most likely to help organisations improve their culture and business outcomes, then communicate them through clear reports, presentations and internal and external thought leadership Create reusable methods, templates and assets; improve internal processes and practices; and negotiate scope, priorities and timelines to deliver high-quality work You have: An advanced degree (Masters or PhD) in organisational psychology, quantitative social science, economics or a related field, or equivalent applied research experience Applied experience using quantitative research methods on people or workforce data

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