Senior Manager – Data Science

Job not on LinkedIn

🔥 5 minutes ago

🐊 Florida – Remote

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⏰ Full Time

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

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👻 Ghost score 12%

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Logo of PODS

PODS

1001 - 5000 employees

🏨 Hospitality

🏗️ Construction

✈️ Travel

💰 Seed on 2022-01

Hospitality • Construction • Travel

PODS is a moving and storage company offering portable, weather-resistant containers delivered to customers' locations for DIY packing, monthly rental, and optional storage at secure, climate-controlled Storage Centers. They provide various container sizes (8', 12', 16'), ground-level loading, tie-downs, and optional professional loading/unloading assistance, and support local and long-distance moves, storage-only services, financing, and online move management.

📋 Description

• 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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