Client Data Analyst II

Role Overview

Mosaic is seeking a Client Data Analyst II to collaborate with clients and internal teams on strategy, analytics, and actionable insights. This role involves developing measurement approaches, analyzing complex datasets, and utilizing findings to optimize program performance while supporting sales and marketing objectives.

Key Responsibilities

• Apply advanced statistical methods to analyze complex datasets, identify business drivers, and develop actionable recommendations for clients and internal stakeholders.
• Lead the development and evolution of measurement frameworks, KPIs, and analytical methodologies to evaluate program performance and business outcomes.
• Design, execute, and interpret quantitative research studies, including market testing, A/B testing, multivariate experiments, and quasi-experimental analyses.
• Build and validate statistical models to understand customer behavior, sales performance, promotional effectiveness, and other key business questions.
• Conduct hypothesis testing, regression analysis, forecasting, segmentation, and other advanced analytical techniques to support strategic decision-making.
• Translate analytical findings into compelling business narratives, communicating insights, risks, assumptions, and recommendations to both technical and non-technical audiences.
• Partner with clients and cross-functional teams to identify opportunities for optimization and develop data-driven go-to-market strategies.
• Stay current on analytical best practices, emerging statistical methodologies, consumer insights research, and industry trends.
• Collect, integrate, cleanse, transform, and validate large, complex datasets from multiple sources while ensuring data quality and integrity.
• Develop reproducible analytical workflows and documentation to support ongoing measurement, research, and reporting initiatives.
• Participate in client meetings, internal strategy sessions, and occasional field ride-alongs to maintain a strong understanding of program operations and business objectives.
• Utilize statistical and analytical software such as Python, R, SQL, and visualization tools to conduct analyses and communicate results.