Senior Manager - Data Science

PODS; Clearwater (FL); On-site; USD 140,000 - 190,000; Full time

Job summary

PODS is seeking a Senior Manager to own the roadmap for Pricing & Revenue Science and lead the development of models that explain and forecast demand, price sensitivity, and revenue performance. You will design experiments, build forecasts, and partner with Product, Engineering, IT, Finance, and Marketing to turn analysis into scalable decision tools.

You will guide a team of data scientists and analytics professionals, establish rigorous standards for measurement and reproducibility, and

Qualifications

• Deep experience leading applied data science in pricing, revenue management, forecasting, optimization
• Strong hands-on fluency in SQL and Python; R is a plus
• 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; able to evaluate methodology, feature selection, validation approaches, explainability, and business applicability
• Familiarity with modern data science tooling and environments, including the Python analytics ecosystem (e.g., pandas, NumPy, scikit-learn, statsmodels or equivalents), cloud data warehouse/lake platforms, and Git/version control
• Ability to partner with Engineering and IT to productionize analytical models and decision systems, with working knowledge of data pipelines, APIs, model monitoring, drift, data quality, and deployment lifecycle practices
• Ability to translate complex technical findings into clear business recommendations and influence senior leaders and cross-functional stakeholders using data-driven insights
• Proven track record leading high-impact analytical initiatives from discovery through implementation and developing data scientists and analysts with strong standards for rigor, documentation, and reproducibility

Responsibilities

• Own roadmap for Pricing & Revenue Science.
• Develop and apply models to explain and forecast demand, conversion, price sensitivity, utilization, and revenue.
• Design pricing experiments; build forecasts; develop optimization approaches that balance conversion, margin, and capacity.
• 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 to translate analytical work into scalable decision tools and operating processes.
• Lead root-cause analysis when performance shifts, communicate recommendations to senior leaders, and coach a high-performing team of data scientists and analytical professionals.

Skills

SQL & Python

Statistics & Econometrics

Predictive Modeling

Elasticity Modeling

Data Science Tooling

Model Deployment

Business Communication

Leadership & Mentorship

Education

Bachelor's degree in Data Science or related field

Master's degree or PhD preferred

Tools

SQL

Python

R

Git

Cloud data warehouses

Job description

Essential Duties And Responsibilities

The Senior Manager will own the roadmap for Pricing & Revenue Science and lead the development and application of models that explain and forecast demand, conversion, price sensitivity, utilization, and revenue performance. Responsibilities include designing pricing and business experiments; building demand and revenue forecasts; developing optimization approaches that balance conversion, margin, and capacity; and creating analytical frameworks that quantify the impact of geography, mileage, seasonality, inventory availability, customer segment, competitive conditions, and other business drivers. This leader will establish standards for causal measurement, model validation, data quality, reproducibility, monitoring, and post-deployment performance. The role partners closely with Product, Engineering, IT, Finance, Operations, Marketing, and other business teams to translate analytical work into scalable decision tools and operating processes. The Senior Manager will also lead root-cause analysis when performance shifts, communicate recommendations to senior leaders, and coach a high-performing team of data scientists and analytical professionals.

The Senior Manager will own the roadmap for Pricing & Revenue Science and lead the development and application of models that explain and forecast demand, conversion, price sensitivity, utilization, and revenue performance. Responsibilities include designing pricing and business experiments; building demand and revenue forecasts; developing optimization approaches that balance conversion, margin, and capacity; and creating analytical frameworks that quantify the impact of geography, mileage, seasonality, inventory availability, customer segment, competitive conditions, and other business drivers. This leader will establish standards for causal measurement, model validation, data quality, reproducibility, monitoring, and post-deployment performance. The role partners closely with Product, Engineering, IT, Finance, Operations, Marketing, and other business teams to translate analytical work into scalable decision tools and operating processes. The Senior Manager will also lead root-cause analysis when performance shifts, communicate recommendations to senior leaders, and coach a high-performing team of data scientists and analytical professionals.

MANAGEMENT & SUPERVISORY RESPONSIBILTIES

• Reports to Vice President, Digital
• Directly manages the Pricing & Revenue Science Team, including Data Scientists and pricing/revenue analytics professionals. Full management authority including hiring, performance management, compensation decisions, and terminations. Responsible for team priorities, analytical standards, and vendor/partner oversight as applicable.

JOB QUALIFICATIONS: Essential Skills, Abilities and Example Behavior(s)

• 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; able to review complex queries, notebooks, model code, and analytical pipelines. Experience with R or another statistical language is a plus
• 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; able to evaluate methodology, feature selection, validation approaches, explainability, and business applicability
• Familiarity with modern data science tooling and environments, including the Python analytics ecosystem (e.g., pandas, NumPy, scikit-learn, statsmodels or equivalents), cloud data warehouse/lake platforms, and Git/version control
• Ability to partner with Engineering and IT to productionize analytical models and decision systems, with working knowledge of data pipelines, APIs, model monitoring, drift, data quality, and deployment lifecycle practices
• Ability to translate complex technical findings into clear business recommendations and influence senior leaders and cross-functional stakeholders using data-driven insights
• Proven track record leading high-impact analytical initiatives from discovery through implementation and developing data scientists and analysts with strong standards for rigor, documentation, and reproducibility

JOB QUALIFICATIONS: Education & Experience Requirements

• Bachelor's degree required in Data Science, Statistics, Computer Science, Economics, Applied Mathematics, Operations Research, Engineering, or a related quantitative field; Master's degree or PhD preferred but not required
• 8+ years of experience in data science, pricing analytics, revenue management, forecasting, optimization, or advanced analytics, with at least 3 years leading or managing data scientists or analytical professionals
• Experience applying predictive, experimental, forecasting, or optimization methods to high-volume commercial or operational decisions; experience in e-commerce, marketplaces, logistics, services, pricing, or revenue management preferred

Physical Requirements

• Ability to sit at a desk and use a computer for extended periods; vision sufficient to view details on a computer monitor
• Ability to stand and walk up to 8 hours a day; ability to 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

WORKING CONDITIONS

• Regular business hours. Some additional hours may be required.
• Travel requirements: Negligible
• Climate-controlled office environment during normal business hours.
• Regular attendance and punctuality required
• May be subject to pre-employment criminal background check and/or drug screening as well as random drug screenings in accordance with company policy

DISCLAIMER

The preceding job description has been designed to indicate the general nature of work performed; the level of knowledge and skills typically required; and usual working conditions of this position. It is not designed to contain, or be interpreted as, a comprehensive listing of all requirements or responsibilities that may be required by employees in this job.

Equal Opportunity, Afficiative Action Employer

PODS Enterprises, LLC is an Equal Opportunity, Afficiative Action Employer. We will not discriminate unlawfully against qualified applicants or employees with respect to any term or condition of employment based on race, color, national origin, ancestry, sex, sexual orientation, age, religion, physical or mental disability, marital status, place of birth, military service status, or other basis protected by law.