PODS is seeking a Data Scientist II to join the Revenue Science team in Clearwater, Florida. This on-site role will own pricing analytics end-to-end—framing business questions, selecting methods, building models, and delivering recommendations that drive pricing decisions across our long-distance and local moving services. You will work with Snowflake and Python, design experiments, and collaborate with pricing analysts and product managers to raise the team’s technical bar. Key responsibilities: - Own models and analyses informing pricing decisions: estimate price elasticity at corridor, segment, and channel levels; develop conversion, demand, and forecasting models accounting for price, mix, channel, and seasonality; quantify the impact of pricing actions on conversion, container utilization, and lifetime revenue; translate results into actionable guidance for commercial leadership. - Lead experiment design and causal measurement: design end-to-end A/B tests (power calculations, exposure rules, metrics) with minimal oversight; apply causal methods (difference-in-differences, synthetic control, regression discontinuity) when randomization isn’t feasible; translate test results into clear recommendations with quantified uncertainty. - Build durable analytical assets: write well-structured Python code (pandas, scikit-learn, statsmodels or equivalents); design and own Snowflake data models; build dashboards and automate recurring analyses. - Communicate and mentor: present results to the Director of Pricing Strategy and Analytics, the Revenue Science team, and senior stakehol

PODS is seeking a Data Scientist II to join the Revenue Science team in Clearwater, Florida. This on-site role will own pricing analytics end-to-end—framing business questions, selecting methods, building models, and delivering recommendations that drive pricing decisions across our long-distance and local moving services. You will work with Snowflake and Python, design experiments, and collaborate with pricing analysts and product managers to raise the team’s technical bar. Key responsibilities: - Own models and analyses informing pricing decisions: estimate price elasticity at corridor, segment, and channel levels; develop conversion, demand, and forecasting models accounting for price, mix, channel, and seasonality; quantify the impact of pricing actions on conversion, container utilization, and lifetime revenue; translate results into actionable guidance for commercial leadership. - Lead experiment design and causal measurement: design end-to-end A/B tests (power calculations, exposure rules, metrics) with minimal oversight; apply causal methods (difference-in-differences, synthetic control, regression discontinuity) when randomization isn’t feasible; translate test results into clear recommendations with quantified uncertainty. - Build durable analytical assets: write well-structured Python code (pandas, scikit-learn, statsmodels or equivalents); design and own Snowflake data models; build dashboards and automate recurring analyses. - Communicate and mentor: present results to the Director of Pricing Strategy and Analytics, the Revenue Science team, and senior stakehol