Data Scientist - Pricing & Revenue Optimization
Role Overview
We are seeking a highly analytical and commercially driven Data Scientist to join our Regional Pricing & Products team. This role is critical to driving profitable growth, yield optimization, and customer retention through advanced analytics, machine learning, and experimentation.You will support the design and deployment of pricing models that enhance willingness-to-pay estimation, optimize customer lifetime value, and proactively identify risks to revenue and margin across customer segments. This position requires a strong combination of data science expertise, business acumen, and the ability to translate insights into actionable pricing strategies.
Key Responsibilities
Develop and enhance willingness-to-pay (WTP) models using machine learning techniques.Analyze customer behavior, shipment characteristics, and competitive dynamics to improve pricing precision.Build segmentation-based pricing strategies to maximize yield while maintaining competitiveness.
Design optimization models to balance volume growth vs. margin expansion.Implement dynamic pricing strategies tailored to customer segments and product lines.
Develop predictive models to identify churn risk and retention opportunities.Design and evaluate pricing experiments (A/B testing, elasticity testing) to improve customer stickiness.
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.
Build and manage pricing experimentation frameworks.Collaborate with IT and data engineering to deploy models into production environments.
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 transformationExperience with:Machine learning models (regression, classification, clustering)Optimization techniques (linear programming, pricing optimization)Time-series forecastingKnowledge of:A/B testing and experimentation designElasticity modeling and demand forecastingFamiliarity with big data tools (e.g., Spark) and cloud environments is a plus
Analytical & Business Skills
Strong understanding of pricing strategy and revenue management principlesAbility to connect modeling outputs to commercial outcomesExperience in customer segmentation and behavioral analytics
Soft Skills
Excellent communication and storytelling skills with dataAbility to influence senior stakeholdersStrong collaboration in cross-functional, global teamsHigh level of ownership and results orientation
Experience & Qualifications
Bachelor's degree in Data Science, Statistics, Economics, Engineering, Mathematics, or related field4-8+ years of experience in data science, preferably in:Pricing / revenue managementLogistics, transportation, airlines, or e-commerce industriesProven track record of:Deploying predictive models in productionDriving measurable business impact (revenue growth, margin improvement, retention)Experience working with commercial or pricing teams is highly desirable