Senior Data Scientist, Special Projects

What you'll do

• Analyze and model large volumes of multi-modal data from devices and cloud systems to identify trends and anomalies.
• Build interactive dashboards, visualizations, and metrics to help engineering teams evaluate system behavior.
• Develop search, retrieval, and indexing strategies to make large-scale data more accessible and actionable.
• Design evaluation frameworks, KPIs, and diagnostics to assess data quality and model performance with AI engineers.
• Collaborate with cloud engineers to determine how data is organized, stored, and exposed for efficient querying.
• Investigate data quality issues and define validation strategies to improve collection and pipeline design.
• Translate complex technical findings into clear written analyses and visual stories for cross-functional stakeholders.

What we're looking for

• Bachelor's or Master's degree in Data Science, Computer Science, Applied Mathematics, or a related field.
• 5+ years of industry experience in data science, analytics engineering, or applied research roles.
• Strong proficiency in Python and common data analysis libraries.
• Expertise with data visualization tools and frameworks for building interactive dashboards.
• Experience querying and modeling data in SQL and NoSQL environments.
• Ability to analyze large-scale, high-dimensional, and multi-modal datasets.
• Familiarity with designing or using search and retrieval systems for large-scale data.
• Experience designing KPIs, evaluation metrics, or experiment analyses for complex systems.
• Strong statistical intuition including exploratory data analysis and hypothesis testing.
• Experience working with data from distributed/real-time systems, robotics, or multi-modal AI (preferred).
• Familiarity with information retrieval techniques like ranking, embedding-based search, and relevance modeling (preferred).
• Knowledge of metadata management, cataloging, or data documentation strategies (preferred).
• Background in statistical modeling, time-series analysis, or anomaly detection (preferred).
• Understanding of cloud-scale data processing and distributed compute frameworks (preferred).