Strategy & Value Consultant - Data Analyst

Data Mapping and Modeling:

• Map and document our data landscape — product usage, customer, CRM, and third-party sources — including schemas, definitions, grain, coverage, and known quality issues
• Design and build analysis-ready tables and data models the wider team can query without re-deriving logic every time
• Establish and maintain consistent metric definitions so the same question returns the same answer across dashboards, value models, and published research
• Own data quality: validation, reconciliation against source systems, and monitoring for breaks

Data Engineering and Operationalization:

• Build and maintain repeatable pipelines to extract, transform, and load data from a variety of sources, including APIs, flat files, and third-party datasets
• Turn one-off analyses into maintained datasets with automated refreshes
• Optimize queries and models for performance against large tables
• Document transformation logic end to end so any published number can be traced back to source

Analysis:

• Perform complex analyses on large datasets: segmentation, cohort and time-series analysis, significance testing, correlation, and regression
• Produce the quantitative foundation for industry benchmarks, maturity models, and industry-specific value models
• Supply the datasets, analyses, and methodology notes behind our white papers and research reports, partnering with the team member who writes them

Dashboards and Reporting:

• Create and maintain dashboards for internal use, focused on customer benchmarks, performance metrics, and presales reporting
• Build reporting stakeholders can self-serve, rather than re-requesting the same cut of data
• Be the team's go-to resource for all data needs

Collaboration and Communication:

• Work with internal stakeholders to identify key data requirements and make sure data is accurate and consistent
• Partner with cross-functional teams (Marketing, Product, Engineering, and Revenue Operations) to get access to the data we need and to understand how it's generated
• Explain methodology, assumptions, and caveats clearly to non-technical stakeholders
• Support live enterprise pursuits with the analysis behind tailored, insight-driven customer briefs