Job Description

Job Description:

The Applied Statistician will apply statistical theory, quantitative modeling, and computational methods to analyze advertising, sales, campaign, client portfolio, and market datasets. The role will support GTM and Branding Ads decisions by designing statistical analyses, building forecasting and ROI models, evaluating program performance, developing statistically sound reporting frameworks, and communicating quantitative findings and limitations to technical and non-technical stakeholders.

Responsibilities

- Statistical Modeling & Analysis: Apply advanced statistical methods (regression, causal inference, cohort analysis, and forecasting) to evaluate GTM campaigns, product adoption, and market outcomes.

- Experimental Design & Validation: Design statistical analysis plans, assess data limitations/uncertainty, and validate the robustness of findings before translating them into business recommendations.

- Market Intelligence & Opportunity Sizing: Analyze vertical-level datasets to develop scoring frameworks for client health, account opportunity sizing, and resource allocation.

- Data Engineering & Reproducibility: Clean, manipulate, and analyze large structured datasets using SQL, Python, or R, while maintaining reproducible data workflows and rigorous QA checks.

- Business Intelligence & Reporting: Design dashboards and tracking frameworks with statistically consistent KPI definitions to monitor revenue mix, sales funnels, and program health.

- ROI Modeling & Program Evaluation: Build statistical business cases and conduct pre/post-mortem evaluations to measure the effectiveness and ROI of regional initiatives and product launches.

- Cross-Functional Communication: Translate complex statistical findings into clear visualizations and executive-ready narratives for Sales, Product, and Leadership stakeholders.