Job Details

About Maisa

Maisa AI is an innovative Agentic Process Automation (APA) Platform that enables enterprises to create and deploy bulletproof AI Agents ("Digital Workers") for automating knowledge-intensive processes. Our flagship product, Maisa Studio, streamlines the creation, deployment, and continuous improvement of AI Agents while maintaining full auditability and explainability through our unique "Chain of Work" approach. We're building the future of enterprise automation with a platform that combines deterministic, code-based steps with AI reasoning, providing unprecedented transparency and reliability for mission-critical business processes.

The Role

We're seeking our first Product Data Analyst to establish data-driven product insights for Maisa Studio. As the founding data hire, you'll build the analytics foundation from the ground up, creating the metrics, dashboards, and analytical frameworks that will guide product decisions for our AI-powered automation platform. This role requires deep understanding of AI product analytics, user behavior in complex enterprise software, and the unique challenges of measuring success in agentic AI systems.

You'll work directly with our distributed microservices architecture, analyzing everything from Digital Worker performance to user engagement patterns, helping us understand how enterprises adopt and succeed with AI automation.

Key Responsibilities

Analytics Infrastructure & Strategy

• Design and implement a comprehensive product analytics framework for Maisa Studio
• Establish key product metrics, KPIs, and success measurements for AI Digital Workers
• Build data pipelines and dashboards to track user behavior, worker performance, and platform adoption
• Create the foundational data infrastructure to support product, engineering, and business decisions
• Define data governance and quality standards for product analytics

AI Product Analytics

• Analyze Digital Worker creation, configuration, and deployment patterns
• Track AI reasoning quality, execution success rates, and error patterns across the KPU system
• Measure user adoption of different AI tools, integrations, and workflow configurations
• Analyze the effectiveness of our "Chain of Work" traceability and explainability features
• Monitor AI model performance, token usage, and computational efficiency across workers

User Behavior & Product Insights

• Analyze user journeys through Maisa Studio interface and identify friction points
• Track feature adoption, time-to-value, and user engagement patterns
• Study how different user personas (business users vs. technical users) interact with the platform
• Analyze worker sharing, collaboration, and deployment success patterns
• Identify usage patterns that correlate with customer success and expansion

Performance & System Analytics

• Monitor and analyze system performance metrics across the microservices architecture
• Track API usage patterns, response times, and bottlenecks through Kong Gateway
• Analyze resource utilization across Code Engine, Marathon system, and execution environments
• Monitor data flow patterns through Apache Kafka and identify system optimization opportunities
• Analyze file storage patterns, processing times, and temporary data lifecycle efficiency

Enterprise Adoption Analytics

• Track onboarding funnels and time-to-first-worker-deployment
• Analyze enterprise usage patterns, worker complexity evolution, and scaling behaviors
• Monitor integration usage (third-party APIs, corporate identity systems)
• Study compliance and auditability feature utilization in regulated industries
• Analyze customer health metrics and churn risk indicators

Business Intelligence & Reporting

• Create executive dashboards showing product adoption, user engagement, and business metrics
• Provide data-driven insights for product roadmap prioritization
• Analyze market fit signals and feature request patterns
• Support sales and customer success teams with usage analytics and expansion opportunities
• Generate regular reports on product performance and growth trends

Required Qualifications

• 4+ years of product analytics experience, preferably with AI/ML products or enterprise software
• Strong experience with AI product metrics (model performance, user-AI interaction patterns, automated workflow success)
• Proficiency in SQL and experience with both relational and NoSQL databases (MongoDB, PostgreSQL)
• Experience with data visualization tools (Tableau, Looker, Grafana, or similar)
• Strong programming skills in Python or R for data analysis and automation
• Experience analyzing complex user journeys and enterprise software adoption patterns
• Understanding of statistical analysis, A/B testing, and experimental design
• Experience working with event-driven architectures and real-time data streams

Desired Qualities

• Previous experience as first/early data hire at a technology startup
• Specific experience analyzing AI agent performance, LLM usage patterns, or automation platforms
• Knowledge of enterprise software adoption patterns in regulated industries
• Experience with AWS data services (S3, DocumentDB, EventBridge analytics)
• Familiarity with Apache Kafka for real-time analytics and event stream processing
• Understanding of microservices architecture and distributed systems monitoring
• Experience with product-led growth metrics and enterprise SaaS analytics
• Knowledge of compliance and auditability requirements in data analysis

What We Offer

• Opportunity to shape the future of accountable enterprise AI agents
• Competitive compensation package
• Flat organization focused on impact rather than hierarchy
• Work with cutting-edge computational AI technology
• Dynamic, experienced team of technical experts
• Continuous learning in the rapidly evolving field of Agentic AI

Location

Remote (Spain) / Madrid Remote, Barcelona Remote, Spain Remote

Additional

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