Commercial Analytics Senior Manager

Greenfield Global

Posted 2mo ago

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Own the commercial analytics function: design, build, and roll out reporting suites and dashboards in Power BI
Define and govern targets, goals, and KPIs across marketing and sales
Present results and recommendations to senior leadership with clear, compelling data storytelling
Develop and operationalize analytical models including attribution, segmentation, CLTV, churn/retention, lead scoring, predictive analytics, and causal inference
Design and execute A/B testing and experimentation programs with appropriate statistical methodology
Build and maintain semantic models and data pipelines in Microsoft Fabric and/or Databricks
Manage data quality, hygiene, and governance across CRM and marketing automation platforms
Partner with stakeholders across marketing, sales, operations, and finance to translate business questions into analytical workstreams
Align measurement frameworks and KPI definitions with marketing and sales leads
Train and enable non-technical stakeholders to self-serve on dashboards and interpret reporting outputs

7+ years in commercial analytics, marketing analytics, revenue operations, or a related quantitative discipline
Proficient in Python or R and SQL, with experience across structured and unstructured data formats
Hands-on with Microsoft Fabric and/or Databricks for big data processing, data engineering, and analytics workloads
Skilled in building semantic models, data models, and ETL/ELT pipelines at scale
Proficient in Power BI and PowerQuery for dashboard development and reporting
Familiar with DevOps practices including version control, CI/CD, and environment management
Demonstrated use of AI tools to enhance analytical productivity
Proven experience operationalizing models including marketing attribution, customer segmentation, churn/retention, CLTV, and lead scoring
Experience designing and executing A/B tests and experimentation programs with statistical rigor
Experience in industrial, chemical, life sciences, energy, or related sectors is strongly preferred
Comfort with technically complex subject matter is essential

Exposure to marketing mix modeling, predictive analytics, causal inference, or demand/pipeline forecasting is a plus

Skills