Head of Product Analytics
Speedinvest is a European venture capital firm that invests from seed to growth stage (Series B to pre-IPO), backing founders with sector-specific expertise and a large network of operational support. It leads the majority of its initial investments and continues to support portfolio companies through multiple follow-on rounds as they scale.
About Speedinvest
Speedinvest is a pan-European venture capital investor with specialist investment teams organized around core sectors including AI & Infra, Climate Tech & Industrial Tech, Deep Tech, Fintech & DeFi, Health & Bio, and Marketplaces & Consumer, alongside a dedicated Growth team writing checks from Series B to pre-IPO. The firm emphasizes leading with conviction and long-term capital from day one, leading 85% of its initial investments, participating in 100+ follow-on rounds each year, and backing 70+ Series A companies over the past four years. Speedinvest works with startup founders across Europe and beyond, providing not just capital but network access and growth support, and counts companies like Bitpanda, Moove, cylib, Tide, Gigs, Upvest, and GoStudent among its portfolio.
Skills
About the Role
You will use product data to identify user problems, inform product strategy, and improve adoption and engagement. You will design and analyse experiments, define measurable KPIs, translate revenue goals into product metrics, and assess engagement-to-LTV correlations. You will partner with product managers, analytics engineers, data, engineering, data product, and data science teams to support self-serve analytics for web and app products.
Requirements
- 10+ years of product analytics experience for a digital product
- Product strategy, experimentation, roadmapping, and prioritisation knowledge
- Experience as an analyst and product manager
- SQL proficiency
- Project management skills
- Presentation skills
- Experience leading a team of analysts in product companies
- Statistical analysis skills
- User experience knowledge
Responsibilities
- Conduct hypothesis-driven product discovery using existing usage data
- Design and analyse product experiments
- Review product and feature performance and define measurable KPIs
- Perform exploratory and hypothesis-driven user research data analysis
- Translate revenue goals into business and product KPIs
- Analyse engagement-to-LTV correlations using statistical methods
- Design experiments to drive product adoption and analyse results
- Partner with cross-functional teams to deliver a self-serve event-data analytics platform
- Partner with data science teams to build a KPI statistics engine
Benefits
- Remote-first work
- 25 days of paid annual leave
- 3 additional days for volunteering and learning
- Private health insurance
- Mental health support platform
- FitPass
- Family and friendly leave according to statutory requirements
- Personal learning and development budget
- Share options