Data Scientist – Pricing & Revenue Optimization

Key Responsibilities

• Pricing & Willingness-to-Pay Modeling
• Analyze customer behavior, shipment characteristics, and competitive dynamics to improve pricing precision.
• Build segmentation-based pricing strategies to maximize yield while maintaining competitiveness.
• Revenue Growth & Yield Optimization
• Design optimization models to balance volume growth vs. margin expansion.
• Implement dynamic pricing strategies tailored to customer segments and product lines.
• Customer Retention & Churn Reduction
• Develop predictive models to identify churn risk and retention opportunities.
• Design and evaluate pricing experiments (A/B testing, elasticity testing) to improve customer stickiness.
• Predictive Analytics & Risk Identification
• Analyze trends and forecast customer-level and segment-level revenue patterns.
• Identify early warning signals of top-line and bottom-line risks.
• Propose data-driven mitigation strategies and commercial actions.
• Experimentation & Model Deployment
• Build and manage pricing experimentation frameworks.
• Collaborate with IT and data engineering to deploy models into production environments.
• Stakeholder Collaboration
• Partner with Sales, Pricing, Finance, Operations and Marketing teams to translate insights into action.
• Communicate complex analytical findings to non-technical stakeholders effectively.

Required Skills

• Technical Skills
• Strong expertise in: Python or R (pandas, NumPy, scikit-learn, etc.), SQL for large-scale data extraction and transformation.
• Experience with: Machine learning models (regression, classification, clustering), optimization techniques (linear programming, pricing optimization), time-series forecasting.
• Knowledge of: A/B testing and experimentation design, elasticity modeling and demand forecasting, familiarity with big data tools (e.g., Spark) and cloud environments.
• Analytical & Business Skills
• Strong understanding of pricing strategy and revenue management principles.
• Ability to connect modeling outputs to commercial outcomes.
• Experience in customer segmentation and behavioral analytics.
• Soft Skills
• Excellent communication and storytelling skills with data.
• Ability to influence senior stakeholders.
• Strong collaboration in cross-functional, global teams.
• High level of ownership and results orientation.