Data Scientist II

Experteer Overview In this role you will own end-to-end analytical projects to support pricing decisions across PODS’ moving businesses. You will work with Snowflake and Python to build predictive and demand models, design experiments, and deliver actionable recommendations that inform pricing strategy and revenue. You’ll partner with pricing analysts and product managers to raise analytical standards and impact multi-million dollar decisions. This position combines modeling, experimentation, and production-ready analytics to scale insights across the business. Compensation / Benefits * Independently estimate price elasticity at corridor, segment, and channel levels and defend methodological choices * Develop and maintain conversion, demand, and forecasting models accounting for price, mix, channel, and seasonality * Quantify impact of pricing actions on conversion, utilization, and lifetime revenue; translate results into actionable leadership guidance * Lead end-to-end experiment design including power calculations, exposure rules, and metric definitions * Select and defend causal methods (e.g., difference-in-differences, synthetic control, regression discontinuity) when randomization is not feasible * Build durable analytical assets: well-structured Python (pandas, scikit-learn, statsmodels), version-controlled; design data models in Snowflake used by other analysts * Create dashboards and automate recurring analyses to surface model outputs for operational use * Present results to senior stakeholders and clearly communicate methodology and limitations * Provide informal mentorship and peer review to earlier-career data scientists Tasks * Strong command of regression, GLMs, hierarchical models, and applied ML with ability to defend the right specification * Fluency in causal inference techniques (diD, synthetic control, IV, regression discontinuity) and ability to match method to question * Ability to lead A/B tests end-to-end (power, exposure rules, metrics, interpretation) * Advanced SQL and Python with experience on large tables and well-structured code * Production-minded workflow: git, code review; experience with automating recurring work; exposure to orchestration tools a plus * Experience with AI-enabled workflows and judgment on verification needs * Excellent communication skills to explain methodology to non-technical stakeholders and defend choices * Bachelor in a quantitative field; 5+ years in applied data science or quantitative analytics with pricing, demand, conversion, or revenue work * Experience deploying or automating analytical work (pipelines, production models) is a plus * Experience in moving, logistics, e-commerce, travel/hospitality, or capacity-constrained businesses is a plus Key requirements *

is including power calculations, exposure rules, and metric definitions * Select and defend causal methods (e.g., difference-in-differences, synthetic control, regression discontinuity) when randomization is not feasible * Build durable analytical assets: well-structured Python (pandas, scikit-learn, statsmodels), version-controlled; design data models in Snowflake used by other analysts * Create dashboards and automate recurring analyses to surface model outputs for operational use * Present results to senior stakeholders and clearly communicate methodology and limitations * Provide informal mentorship and peer review to earlier-career data scientists Tasks * Strong command of regression, GLMs, hierarchical models, and applied ML with ability to defend the right specification * Fluency in causal inference techniques (diD, synthetic control, IV, regression discontinuity) and ability to match method to question * Ability to lead A/B tests end-to-end (power, exposure rules, metrics, aaaaaaaaaa raise * Advanced SQL and Python with experience on large tables and well-structured code * Production-minded workflow: git, code review; experience with automating recurring work; exposure to orchestration tools a plus * Experience with AI-enabled workflows and judgment on verification needs * Excellent communication skills to explain methodology to non-technical stakeholders and defend choices * Bachelor in a quantitative field; 5+ years in applied data science or quantitative analytics with pricing, demand, conversion, or revenue work * Experience deploying or automating analytical work (pipelines, production models) is a plus * Experience in moving, logistics, e-commerce, travel/hospitality, or capacity-constrained businesses is a plus Key requirements *