PODS Enterprises, LLC is seeking a Data Scientist I to join the Revenue Science team in Clearwater, Florida. In this onsite role, you will report to the Director of Pricing Strategy and Analytics and help quantify pricing impact using Snowflake, Python, and experiment design.
This position focuses on measuring price elasticity across corridors, segments, and channels, then translating those findings into practical guidance for daily pricing decisions. You will work across modeling, causal analysis, and reporting so that both the Revenue Science team and operational stakeholders can use the results with confidence.
What you’ll do
- Estimate price elasticity at the corridor, segment, and channel level using observational and experimental data.
- Build conversion and demand models that incorporate price, mix, channel, and seasonality.
- Quantify how pricing actions affect conversion, container utilization, and lifetime revenue.
- Collaborate with senior data scientists and pricing analysts on A/B test design, including power calculations, exposure rules, and metric definitions.
- Conduct causal analyses when randomization is not feasible, using methods such as difference-in-differences, synthetic control, or regression discontinuity.
- Translate experiment and causal results into recommendations that include quantified uncertainty.
- Author analyses in Python using modern tooling such as pandas, scikit-learn, and statsmodels (or similar).
- Develop and maintain core data models in Snowflake that other analysts and downstream tools depend on.
- Create dashboards and reports that present model outputs in an actionable way for operational users.
- Present findings to the Director of Pricing Strategy and Analytics and the broader Revenue Science team.
- Explain methodology, results, and limitations in plain language for non-technical stakeholders.
- Document analyses so conclusions are reproducible and reviewable by peers.
Required qualifications
- Education: Bachelor’s degree in a quantitative field (Master’s preferred).
- Experience: 3+ years of applied data science or quantitative analytics experience, including hands-on work on pricing, demand, conversion, marketing, or revenue problems.
- Hands-on experience with SQL on a modern cloud data warehouse (Snowflake preferred) and with Python for analysis.
- Ability to work with regression, generalized linear models, and applied ML techniques, with good judgment about which approach fits the question.
- Working knowledge of quasi-experimental techniques such as difference-in-differences, synthetic control, instrumental variables, or regression discontinuity, and the ability to select an appropriate method.
- Hands-on A/B testing experience, including power calculations, metric definitions, and interpreting results.
- Demonstrated use of AI tools (such as Claude, Cursor, or Copilot) to accelerate code, query, and documentation, with the judgment to verify AI output.
- Ability to explain methodology and results to non-technical stakeholders in writing and in person.
Helpful additional experience
- Experience with multiple causal inference techniques or applied Bayesian methods.
- Experience in moving, logistics, e-commerce, travel/hospitality, or other capacity-constrained consumer businesses.
Technology and tools
- Snowflake, Python, pandas, scikit-learn, statsmodels, SQL
- A/B testing, difference-in-differences, synthetic control, regression discontinuity
- Claude, Cursor, Copilot
Management & supervisory responsibilities: This role does not have direct reports and reports to the Director of Pricing Strategy and Analytics.
Other duties: Other duties as assigned.