Technical Product Manager- Analytics

Location: Berlin, Germany  Remote Status: Fully Remote (#LI-Remote)

LivePerson (NASDAQ: LPSN) is a leader in trusted enterprise conversational AI and digital transformation. The world's leading brands use our award-winning Conversational Cloud platform to connect with millions of consumers. We power nearly a billion conversational interactions every month, providing uniquely rich data analytics and safety tools to unlock the power of conversational AI for better business outcomes. Fast Company named LivePerson the #1 Most Innovative AI Company in the world.

Position Overview

As a Technical Product Manager, you will join the LivePerson Analytics Product team and be responsible for the Analytics suite, including Data services, Analytics Studio, Report Center, Data Transporter etc. The core responsibility is to define the strategy and execution for tools and services that leverage conversational data to provide actionable customer and internal insights.

As the Technical Product Manager for Analytics, you will lead the development and execution of our Analytics capabilities, focusing on leveraging conversational data to provide actionable customer and internal insights. You will collaborate closely with cross-functional teams, including Engineering, Data Science, Sales, and Customer Success, to define product strategy, prioritize features, and deliver innovative solutions that ensure scalability, reliability, and best-in-class experiences for brands.

You Will: Key Responsibilities & Impact

• Develop and articulate a clear product vision and strategy for our end-to-end Analytics platform, ensuring it empowers customers and internal teams to gain actionable insights from Conversational Data.
• Define, review, and prioritize features for the Analytic Studio/Builder and Report Center, focusing on an intuitive user experience for data exploration, visualization, and report scheduling.
• Manage the product roadmap for Data Services and Data Transporter, guaranteeing the timely, accurate, and scalable ingestion and preparation of petabyte-scale conversational data streams.
• Work closely with Data Science and Engineering teams to integrate Conversational Intelligence (AI/ML-derived insights) features directly into the core analytics products.
• Define and track key performance indicators (KPIs) and data quality metrics for all data pipelines and analytic tools, ensuring high data reliability, freshness, and tool usage.
• Act as the primary interface between Analytics users (internal and external) and the Data Engineering teams, translating complex data requirements into clear, technical specifications.

You Have: Required Skills & Qualifications

• Bachelor's degree in Computer Science, Engineering, Business, or a related field (MBA preferred).
• 7+ years of experience in product management, with a track record of successfully launching and managing SaaS analytics and reporting products or platforms.
• Deep understanding of data warehousing, business intelligence (BI) tools, reporting systems, high-scale data processing, event-driven architectures, and cloud infrastructure.
• Proven ability to develop and execute product strategy for data and analytics products, prioritize features, and drive product roadmap planning in a fast-paced, agile environment.
• Strong analytical skills, with the ability to gather and interpret data, identify trends in product usage, and make data-driven decisions.
• Excellent communication, collaboration, and leadership skills, with the ability to influence and inspire cross-functional teams (e.g., Data Engineering, Data Science, Design).
• Experience working with enterprise customers on their reporting and analytics needs and a strong customer focus, with the ability to empathize with customer data consumption pain points.
• Passion for innovation, creativity, and solving complex data and reporting challenges to deliver impactful, self-service solutions.

Product Coverage Scope:

• Report Center & Analytic Studio/Builder: Tools for creating, visualizing, and sharing reports, dashboards, and custom analytics using conversational data.
• Data Transporter & Data Services: Infrastructure and pipelines for extracting, transforming, and loading (