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 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 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 Qualifications

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

Technical Skills

• Analytics Tools: SQL, Python/R, Jupyter notebooks, statistical analysis libraries

• Databases: MongoDB, PostgreSQL, Redis, experience with document and time-series data

• Visualization: Tableau, Looker, Grafana, or similar BI tools

• Cloud Platforms: AWS services (S3, DocumentDB, CloudWatch), experience with cloud analytics

• Data Processing: Experience with ETL/ELT pipelines, real-time data processing

• APIs: REST/GraphQL API analysis, understanding of API usage patterns

• Monitoring: Familiarity with Prometheus, Grafana, Sentry for system analytics

• Version Control: Git for analytics code and documentation