Applied Scientist
Core
Transform large commercial datasets into actionable insights for leadership to drive pricing, distribution, and investment decisions in the vaping industry.
Role type
Applied Scientist (Commercial Analytics & Causal Inference)
Builds
Market-share and demand forecasting models, predictive models for field operations, and internal data tools democratizing access to commercial data.
Domain
Consumer Packaged Goods (CPG) / Retail / Syndicated Market Data
Deliverable
production ML models | dashboards & analysis
Required skills
SQL, Python (pandas), experimental design, causal inference, statistical analysis, data modeling, AI/LLM tooling
Preferred skills
Analytics engineering (version control, testing, documentation), commercial/retail/CPG domain knowledge, modern data ecosystem familiarity
Technologies
SQL, dbt, BigQuery, Python, LLMs, AI agents
Responsibilities
Partner with commercial/finance/executive stakeholders to transform business questions into analytical problems; Design and run rigorous experimental/quasi-experimental analyses (Diff-in-Diff, propensity methods) to measure causal impact; Architect and maintain large commercial datasets and build forecasting models; Build predictive models guiding field sales operations; Deploy LLMs and AI agents to classify unstructured commercial data.
Seniority
Mid-Senior (5+ years experience)
