Senior Vice President, Data Science

Employment Type: Full-Time
Location: Onsite – Atlanta, GA

About the Role

We are seeking a visionary and hands-on Senior Vice President of Data Science to lead the strategy, development, and execution of advanced pricing, forecasting, and optimization capabilities across a rapidly growing technology platform.

This executive leadership role will be responsible for building and scaling a world-class Data Science organization focused on transforming large-scale transactional and behavioral data into actionable pricing intelligence and revenue optimization solutions. The ideal candidate combines deep quantitative expertise with strong commercial acumen and has a proven track record of building production-grade machine learning and optimization systems that drive measurable business outcomes.

You will serve as a strategic partner to Product, Engineering, Revenue, and Executive Leadership, helping define how data science creates long-term competitive advantage and enterprise value.

What You’ll Do

Pricing & Revenue Optimization Strategy

• Define and execute the long-term vision for pricing science, forecasting, and revenue optimization.
• Develop sophisticated pricing models that maximize revenue, inventory utilization, and customer value.
• Create dynamic forecasting and demand prediction models that adapt to changing market conditions.
• Build methodologies for measuring pricing performance, revenue impact, forecast accuracy, and model effectiveness.
• Establish guardrails, business rules, and decision frameworks that balance automation with operational oversight.

Data Science Leadership

• Build, lead, and mentor a high-performing team of Data Scientists, Machine Learning Engineers, Quantitative Analysts, and related technical talent.
• Establish standards, methodologies, and best practices for model development and deployment.
• Foster a culture of experimentation, innovation, accountability, and continuous learning.
• Drive the professional growth and development of technical teams while maintaining a high bar for scientific rigor.

Machine Learning & Advanced Analytics

• Apply machine learning, statistical modeling, optimization techniques, and experimentation frameworks to complex business challenges.
• Develop models that leverage transactional, inventory, customer, and market data to improve decision-making.
• Design systems that continuously improve as new data becomes available.
• Evaluate emerging technologies and methodologies that can create strategic advantages.

Productization & Platform Integration

• Partner closely with Product and Engineering teams to transform research into scalable production systems.
• Ensure models are explainable, measurable, auditable, and suitable for enterprise deployment.
• Establish model monitoring, validation, retraining, and continuous improvement processes.
• Support the development of automated decisioning systems capable of operating at scale.

Data & Market Intelligence

• Build frameworks for extracting insights from large and complex datasets.
• Assess new internal and external data sources to improve predictive performance.
• Identify market patterns, customer behaviors, and revenue opportunities through advanced analytics.
• Develop analytical capabilities that support strategic planning and operational decision-making.

Executive & Commercial Leadership

• Partner with executive stakeholders to align data science initiatives with business objectives.
• Translate complex quantitative findings into actionable business recommendations.
• Influence company strategy through data-driven insights and performance analytics.
• Serve as a key leader in identifying opportunities to drive growth, profitability, and competitive differentiation.

Required Qualifications

• 10+ years of experience in Data Science, Machine Learning, Quantitative Analytics, Pricing Science, Revenue Management, or a related discipline.
• Proven experience developing and deploying pricing, forecasting, optimization, or recommendation models in commercial environments.
• Deep expertise in:
  • Statistical Modeling
  • Machine Learning
  • Time-Series Forecasting
  • Optimization Techniques
  • Experimentation Frameworks
  • Predictive Analytics
• Experience working with large-scale transactional, customer, and behavioral datasets.
• Demonstrated success building and leading Data Science teams.
• Strong understanding of pricing strategy, demand forecasting, inventory optimization, and revenue management principles.
• Experience partnering closely with Product and Engineering organizations.
• Exceptional communication skills with the ability to influence executive stakeholders.
• Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, Engineering, Operations Research, or a related quantitative field.

Preferred Qualifications

• Advanced degree (Master’s or Ph.D.) in a quantitative discipline.
• Experience in industries involving:
  • Dynamic Pricing
  • Marketplaces
  • Travel
  • Hospitality
  • Sports & Entertainment
  • E-commerce
  • Financial Markets
  • Revenue Management
• Expertise in:
  • Price Elasticity Modeling
  • Reinforcement Learning
  • Recommendation Systems
  • Causal Inference
  • Operations Research
  • Sequential Decision-Making Systems
  • MLOps and Model Governance
• Experience supporting enterprise-scale machine learning platforms.