Senior Manager – Data Science

This is a fully remote position, open to applicants in Florida.

📋 Description

• Take ownership of the roadmap for Pricing & Revenue Science.

• Lead the creation and implementation of models that explain and forecast demand, conversion rates, price sensitivity, utilization, and revenue performance.

• Design and execute pricing and business experiments.

• Develop forecasts for demand and revenue.

• Create optimization strategies that balance conversion rates, margins, and capacity.

• Establish analytical frameworks that assess geography, mileage, seasonality, inventory availability, customer segments, competitive conditions, and other business drivers.

• Set standards for causal measurement, model validation, data quality, reproducibility, monitoring, and post-deployment performance evaluation.

• Collaborate with Product, Engineering, IT, Finance, Operations, Marketing, and other business teams.

• Convert analytical insights into scalable decision-making tools and operational processes.

• Lead root-cause analysis when there are shifts in performance.

• Present recommendations to senior leadership.

• Mentor a high-performing team of data scientists and analytical experts.

• Directly oversee the Pricing & Revenue Science Team, which includes Data Scientists and pricing/revenue analytics professionals.

• Make decisions regarding hiring, performance management, compensation, and terminations.

• Establish team priorities and analytical standards.

• Oversee vendors and partners as necessary.

• Report to the Vice President, Digital.

⛳️ Requirements

• A Bachelor's degree is required in Data Science, Statistics, Computer Science, Economics, Applied Mathematics, Operations Research, Engineering, or a related quantitative discipline.

• Over 8 years of experience in data science, pricing analytics, revenue management, forecasting, optimization, or advanced analytics.

• At least 3 years of experience in leading or managing data scientists or analytical professionals.

• Extensive experience in applied data science or decision science within pricing, revenue management, forecasting, optimization, marketplace economics, or a relevant analytical area.

• Proficient hands-on experience with SQL and Python.

• Strong understanding of statistics and applied econometrics, including regression analysis, hypothesis testing, causal inference, experimental design, measurement, and model validation.

• Experience in predictive modeling, machine learning, forecasting, elasticity modeling, and optimization techniques.

• Familiarity with Python analytics libraries such as pandas, NumPy, scikit-learn, and statsmodels or their equivalents.

• Knowledge of cloud data warehouse/lake platforms and version control systems like Git.

• Working knowledge of data pipelines, APIs, model monitoring, drift, data quality, and deployment lifecycle best practices.

• Experience applying predictive, experimental, forecasting, or optimization methods to high-volume commercial or operational decisions.

• Ability to successfully pass pre-employment criminal background checks and/or drug screenings, as well as random drug tests per company policy.

• Capability to sit at a desk and use a computer for extended periods.

• Ability to stand and walk for up to 8 hours a day, stoop, bend, and lift boxes weighing up to 50 lbs.

• Ability to hear and communicate verbally using a telephone handset and/or connected headset device.

• Regular attendance and punctuality are required.

• Some additional hours may be necessary.

🏝️ Benefits

• Full-Time employment.

• Remote work arrangement available.

• Climate-controlled office environment during regular business hours.

• Equal Opportunity, Affirmative Action Employer.