Director - Pricing Strategy & Revenue Science

PODS; Clearwater (FL); On-site; USD 180,000 - 240,000; Full time

Job summary

PODS is seeking a Director of Pricing Strategy & Revenue Science to lead a data-driven pricing function that improves conversion, margin, and utilization across customer interactions. You will build models forecasting demand, price sensitivity, and revenue performance while designing experiments and governance frameworks.

You will partner with Product, Engineering, IT, Finance, Operations, and Marketing to translate analytics into scalable tools and decision processes and coach a high-performing

Qualifications

• Bachelor's degree in a quantitative field.
• 8+ years in data science, pricing analytics or related fields.
• Experience leading data scientists or analytics teams.
• Customer-facing experience is required.
• Strong SQL and Python skills.

Responsibilities

• Lead pricing strategy and revenue science team.
• Design pricing experiments and develop forecasts.
• Partner with Product, IT, Finance, and Ops.
• Translate analyses into scalable decision tools.
• Mentor and develop analytics talent.

Skills

SQL fluency

Python programming

R knowledge

Statistics & econometrics

Predictive modeling

Experiment design

Optimization

Data storytelling

Cross-functional leadership

Customer facing

Education

Bachelor's in quantitative field

Advanced degree preferred (MS/PhD)

Tools

pandas

NumPy

scikit-learn

statsmodels

Git

Job description

Director, Pricing Strategy & Revenue Science

Build the Future of Pricing at PODS

At PODS, we’re transforming how pricing drives growth, customer experience, and competitive advantage across our business. We’re looking for a visionary, analytically-driven leader to modernize and elevate our pricing capabilities from a primarily manual, rules-based model into a sophisticated, data-driven pricing function that improves conversion, margin and network utilization across every customer interaction.

As the Director of Pricing Strategy & Revenue Science, you will 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 Director 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.

What You’ll Do

MANAGEMENT & SUPERVISORY RESPONSIBILTIES

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

Day To Day, You Will

• 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, explain ability, and business applicability
• Familiarity with modern data science tooling and environments, including the Python analytics ecosystem (e.g., pandas, NumPy, scikit-learn, stats models 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

Who We’re Looking For

We’re looking for a strategic thinker who combines strong analytical capabilities with business acumen, executive presence, and leadership skills. Prior pricing experience is valued but not required; the ability to rapidly learn a new domain, build a product roadmap with actual milestones, and lead a team that does rigorous work is essential. This is a high-autonomy, high-accountability role at the intersection of strategy, data, and execution.

What You Bring

• You've built strategy roadmaps where success was defined upfront, not rationalized afterward
• You can read SQL, spot a flawed methodology, and tell the difference between a real trend and a composition effect
• You've delivered cross-functional initiatives end to end, not handed off after the strategy deck was done
• You know when the data is good enough to act and when more investigation is the right call; when you hit ambiguity, your instinct is to investigate, not wait
• You've hired and developed analytical talent, and people have grew under your leadership
• Must have customer facing experience.
• 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

Why You’ll Love Working at PODS

PODS is a recognized leader in the moving and storage industry, known for innovation, operational excellence, and a strong people-first culture. We believe strong teams drive strong results. At PODS, you’ll find a culture built on collaboration, accountability, integrity, and continuous improvement. Our core values – We Care, We Work as a Team, and We Find a Way – are the guiding principles behind everything we do.

Compensation & Benefits

PODS offers a competitive compensation package that includes medical, dental, and vision coverage, a 401(k) with company match, bonus opportunities, paid time off, and employee storage discounts. Compensation is based on experience, qualifications, and internal equity.

Equal Opportunity Employer

PODS Enterprises, LLC is an Equal Opportunity and