Senior Manager – Data Science
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Job Description
Senior Manager leading pricing and revenue science at PODS, a portable storage company. Forecasting demand, optimizing revenue, and managing data science professionals.
Responsibilities:
- Own the roadmap for Pricing & Revenue Science
- Lead development and application of models explaining and forecasting demand, conversion, price sensitivity, utilization, and revenue performance
- Design pricing and business experiments
- Build demand and revenue forecasts
- Develop optimization approaches balancing conversion, margin, and capacity
- Create analytical frameworks measuring geography, mileage, seasonality, inventory availability, customer segment, competitive conditions, and other business drivers
- Establish standards for causal measurement, model validation, data quality, reproducibility, monitoring, and post-deployment performance
- Partner with Product, Engineering, IT, Finance, Operations, Marketing, and other business teams
- Translate analytical work into scalable decision tools and operating processes
- Lead root-cause analysis when performance shifts
- Communicate recommendations to senior leaders
- Coach a high-performing team of data scientists and analytical professionals
- Directly manage the Pricing & Revenue Science Team, including Data Scientists and pricing/revenue analytics professionals
- Make hiring, performance management, compensation, and termination decisions
- Set team priorities and analytical standards
- Oversee vendors and partners as applicable
- Report to the Vice President, Digital
Requirements:
- Bachelor's degree required in Data Science, Statistics, Computer Science, Economics, Applied Mathematics, Operations Research, Engineering, or a related quantitative field
- 8+ years of experience in data science, pricing analytics, revenue management, forecasting, optimization, or advanced analytics
- At least 3 years leading or managing data scientists or analytical professionals
- Deep experience leading applied data science or decision science work in pricing, revenue management, forecasting, optimization, marketplace economics, or a related analytical domain
- Strong hands-on fluency in SQL and Python
- Strong command of statistics and applied econometrics, including regression, hypothesis testing, causal inference, experimental design, measurement, and model validation
- Experience with predictive modeling, machine learning, forecasting, elasticity modeling, and optimization
- Familiarity with Python analytics tools such as pandas, NumPy, scikit-learn, and statsmodels or equivalents
- Familiarity with cloud data warehouse/lake platforms and Git/version control
- Working knowledge of data pipelines, APIs, model monitoring, drift, data quality, and deployment lifecycle practices
- Experience applying predictive, experimental, forecasting, or optimization methods to high-volume commercial or operational decisions
- Ability to pass pre-employment criminal background check and/or drug screening, and random drug screenings in accordance with company policy
- Ability to sit at a desk and use a computer for extended periods
- Ability to stand and walk up to 8 hours a day, stoop, bend, and lift boxes weighing up to 50 lbs.
- Ability to hear and verbally communicate using a telephone handset and/or connected headset device
- Regular attendance and punctuality required
- Some additional hours may be required
Benefits:
- Full-Time employment
- Remote work arrangement
- Climate-controlled office environment during normal business hours
- Equal Opportunity, Affirmative Action Employer
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