Senior Vice President of Data Science 5637

Tier4 Group; Atlanta (GA); On-site; USD 250,000 - 350,000; Full time

Job summary

Tier4 Group seeks a Senior Vice President of Data Science to lead pricing, forecasting, and optimization across a rapid-growth technology platform.

You will build and scale a world-class data science organization, translating large-scale data into pricing intelligence and revenue enhancement. The role partners with Product, Engineering, Revenue, and Executive Leadership to create competitive advantage.

Qualifications

• 10+ years of experience in Data Science, ML, or pricing analytics.
• Proven experience deploying pricing, forecasting, optimization models in commercial settings.
• Deep expertise in statistical modeling and time-series forecasting.
• Experience with large-scale transactional, customer, and behavioral data.
• Demonstrated success building and leading Data Science teams.
• Strong understanding of pricing strategy, demand forecasting, inventory optimization, and revenue management.

Responsibilities

• Define and execute long-term pricing science, forecasting, and revenue optimization vision.
• Develop pricing models to maximize revenue, inventory utilization, and customer value.
• Create dynamic forecasting and demand prediction models adapting to market changes.
• Establish measurement of pricing performance, revenue impact, and forecast accuracy.
• Lead and mentor a high-performing Data Science team.
• Partner with Product and Engineering to deploy scalable production systems.
• Ensure models are explainable, auditable, and governance-ready.

Skills

Data science leadership

Pricing science

Revenue management

Machine learning

Time-series forecasting

Statistical modeling

Predictive analytics

Experimentation

Model deployment

Communication skills

Education

Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, Engineering, Operations Research, or related quantitative field

Tools

MLOps

Model governance

Job description

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.
• 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.
• 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.
• 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
• Time-Series Forecasting
• 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
• Revenue Management
• Price Elasticity Modeling
• Recommendation Systems
• Operations Research
• Sequential Decision-Making Systems
• MLOps and Model Governance
• Experience supporting enterprise-scale machine learning platforms.