Senior Product Data Analyst

Bachelor’s degree in Business Operations, Data Science, Statistics, Computer Science, or a related field (or equivalent experience)
12 plus years of experience working with and influencing multi disciplinary teams consisting of but not limited to software engineers, designers, product managers, data scientists, sales, and marketing
Proficient with SQL and Python
Proficient with analytics and BI tools such as Amplitude, Adobe Analytics, and Tableau
Experience developing data pipelines on GCP, Azure, and AWS
Experience stitching open source data from GitHub and Hugging Face with first party data
Familiarity with very large volume of data across multiple data sources
Experience in interpreting complex business questions, analytical thinking, problem solving, and providing recommendations from data
Self-motivated, collaborative, organized and proactive, highly responsive, flexible and adaptable when working across multiple teams
Excellent communication and project management skills

Develop and manage data pipelines and dashboards end-to-end for the NGC and AI Catalog using analytics and BI tools such as Amplitude and Tableau to present data visually
Partner with engineering team to extract, transform, and load data from various data sources, including cloud platforms (GCP, Azure, AWS). Then set up telemetry event tracking, structure event logs, and analyze system-level logs. Collaborate with product managers to prioritize features based on usage patterns
Work with product teams to establish metrics for measuring business performance that support business objectives, offer insights that shape strategy, improve product experiences, and promote long-term growth
Analyze product usages at a detail level, uncovering friction points, identifying underused features, and recommending improvements to UX and functionality
Deliver insights across the entire product lifecycle, including product trials, onboarding, license activation, feature adoption, usage behavior, retention, and churn
Lead initiatives to improve reporting scalability, data integrity, and data quality

Experience using GPU-accelerated libraries such as CUDA, cuDNN, and RAPIDS
Familiarity with CI/CD frameworks, such as Apache Airflow, Jenkins, or Gitlab CI/CD
Knowledge in ML/AI and advanced statistical analysis techniques
Understanding of both enterprise buyers, developers, and the importance of consistency between these groups
Experience leading product growth strategies