Drive business and product planning through insights on product usage, adoption, feature utilization, performance, and reliability.
Design and implement robust data models and schemas aligned to product and platform needs.
Audit existing product, platform, and data systems for completeness and accuracy, and strengthen instrumentation to enable reliable, decision-ready analytics.
Build and optimize scalable data pipelines and architectures, including cloud-based ETL processes and large-scale data structures for analytics and machine learning.
Develop processes to ingest, transform, and distribute data into internal systems and applications.
Partner with engineering and platform teams to identify and resolve data quality issues.
Create dashboards, analyses, and experimentation frameworks that translate raw data into clear recommendations.
Provide rigorous ad hoc analysis to support strategic and operational decisions.
Communicate findings clearly to cross-functional stakeholders and senior leaders.

Bachelor’s or advanced degree in Mathematics, Economics, Computer Science, Information Management, Statistics, or related field.
Significant experience in data science, advanced analytics, or business analytics roles.
Strong expertise in SQL and working with complex, large-scale datasets across multiple sources.
Proficiency with analytics and BI tools such as Looker, Tableau, Splunk, Mixpanel, or similar platforms.
Experience with Python or R for statistical analysis and data processing.
Hands-on experience with big data and cloud-based data environments such as AWS, Redshift, Snowflake, BigQuery, Spark, or similar technologies.
Strong systems thinking / Experience building analytics foundations in complex environments.
Ability to collect, structure, analyze, and interpret large volumes of data with accuracy and attention to detail.
Strong written and verbal communication skills, with the ability to present complex ideas in a clear, actionable way.

Principal Data Scientist

Key skills