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Product lead & Data Analyst

Labhouse
CompanyLabhouse
CategoryData & Analytics
LocationBarcelona
RemoteHybrid
EmploymentNot stated
LevelLead
SalaryNot stated by the employer
Posted20 May 2026
Last verified3 Aug 2026
SourceEmployer ATS (ashby)
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Description
Labhouse is a fast-growing startup that builds, launches, and scales its own AI & Productivity Apps, operating under a subscription-based business model. Based in Barcelona, Labhouse was founded by Andrés Bou and Horacio Martos (Co-Founders of SocialPoint). We operate at the intersection of mobile technology, AI, and product-driven growth, with a strong focus on experimentation and performance. Would you like to make an impact as part of a company that builds the best mobile apps used by millions of users worldwide? If so, discover your next challenge below. Now we're looking for a Product lead & Data Analyst to work side by side with our CEO, turning data into the apps of tomorrow 🚀 ABOUT THE ROLE As Data Product Manager, you'll partner directly with the CEO to launch new apps and evolve our existing portfolio. You'll bring a data-first mindset to product decisions — using user behavior, experimentation, and analytics to identify opportunities, prioritize features, and ship products that scale. This role requires someone highly autonomous, entrepreneurial, and impact-driven, capable of defining KPIs, building dashboards, and making data-informed decisions. You'll be responsible for: - Working hand in hand with the CEO to ideate, validate, and launch new mobile apps - Driving product decisions on existing apps using data, experimentation, and user insights - Defining and tracking the metrics that matter: activation, retention, monetization, LTV - Designing and analyzing A/B tests, onboarding flows, and monetization experiments - Translating raw data into clear product hypotheses and roadmap priorities - Collaborating with engineering, design, and marketing to ship fast and iterate faster - Leveraging AI tools to accelerate research, prototyping, and decision-making ABOUT YOU: Academic background: - Degree in a quantitative or technical field — Data Science, Data Engineering, Computer Science, Engineering, Mathematics, Statistics, Physics, or similar - Strong academic record from a top-tier university What are we looking for: - 2-4 years of experience as a Data Scientist, Data Engineer, or Data Analyst, who has transitioned into product - Solid analytical foundation: SQL, statistics, experimentation, and product metrics (CAC, LTV, retention, ARPU) - A genuine product mindset — you don't just analyze data, you ask why and propose what to build next - High agency, ownership, and bias for action - Comfortable working directly with founders in a fast-paced environment - Strong proficiency with AI tools to accelerate your workflow - Passion for UI/UX and Apple-like product experiences Communication: - Strong level of spoken and written English and Spanish - Clear, structured communicator who can simplify complex data into product narratives NICE TO HAVE: - Experience building products from 0 to 1. - Experience working closely with founders or in startup environments. - Ability to work remote or hybrid (Barcelona-based preferred). WHAT WE OFFER: - The opportunity to work side by side with serial entrepreneurs who've built and exited at the highest level - A real path to becoming a product leader, mentored directly by the CEO - Attractive compensation package, above market average - Hybrid work model from our Barcelona office - A fast-moving, AI-native environment where shipping beats talking HIRING PROCESS 1. TA Interview – Initial conversation to get to know each other and understand your background. 2. Technical Case – Practical exercise to assess your product, analytical, and strategic capabilities. 3. CEO / Product Team Interview – Deep dive into your product thinking, experience, and fit with the team. 4. Final Interview – Final conversation to ensure alignment on expectations, culture, and role fit. YOU SHOULD KNOW: Labhouse is proud to be an equal-opportunity employer. However you identify or whatever