Senior Data Analyst

Cornerstone is seeking a highly analytical and detail-oriented Senior Data Analyst to accelerate analytic projects including strategic reporting, model design and serve as a key data steward to enable AI agent strategies. In this role, you will be essential to delivering data insights and inputs, directly supporting revenue growth and cross-functional Go-To-Market (GTM) strategies in sales, marketing, customer success, and engineering. You will lead efforts to ensure high-quality, well-governed datasets that improve revenue performance tracking and fuel AI agent learning.

In this role you will...

• Champion data exploration and experimentation using advanced techniques such as clustering, regression analysis, and time series modeling.
• Lead and scale data mining initiatives to uncover patterns, trends, and correlations across large, complex datasets.
• Design and build models to support projections, revenue expansion, churn analysis, and other strategic efforts.
• Collaborate with stakeholders to translate business problems into data-driven analytical approaches and clearly communicate results and recommendations.
• Monitor, analyze, and refine the feature store, ensuring data elements leveraged by dashboards and AI models are consistent, version-controlled, and trustworthy.
• Curate, clean, and optimize data inputs used for training and inference in artificial intelligence and machine learning workflows.
• Mentor junior analysts, fostering a culture of data stewardship and responsible AI enablement across the organization.
• Stay current with emerging tools, trends, and methodologies in analytics, data science, and AI.

• 5+ years of experience in a data analyst, data scientist, or data stewardship capacity, ideally in SaaS or enterprise software.
• Expert-level proficiency in SQL and experience querying large, distributed datasets.
• Strong hands-on experience with BI platforms (e.g., Tableau, Looker, Power BI).
• Expert-Level Excel skills and understanding of CRM object relationships including leads, accounts, opportunities, orders and quotes.
• Demonstrated ability to design, build, and validate statistical or predictive models using Python, R, or equivalent tools.
• Strong understanding of data quality management, data lineage, and data governance principles, with proven impact on AI/ML workflows.
• Solid understanding of key modeling techniques such as regression, classification, clustering, and time-series forecasting.
• Strong problem-solving skills with a track record of turning raw data into clear and compelling insights.
• Excellent communication skills with the ability to explain complex technical concepts to non-technical audiences.
• Demonstrated commitment to valuing diversity and contributing to an inclusive working and learning environment
• Consideration for privacy and security obligations