Data Scientist - Pricing & Revenue Optimization

** 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*
* ** 1. Pricing & Willingness-to-Pay Modeling*
* +  
** 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.*
* ** 2. 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.*
* ** 3. 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.*
* ** 4. 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.*
* ** 5. Experimentation & Model Deployment*
* +  
** Build and manage pricing experimentation frameworks.*
* +  
** Collaborate with IT and data engineering to deploy models into production environments.*
* ** 6. 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, Num Py, 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 is a plus*
* ** 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*
* ** Experience & Qualifications*
* +  
** Bachelor's degree in Data Science, Statistics, Economics, Engineering, Mathematics, or related field*
* +  
** 4-8+ years of experience in data science, preferably in:*
* +  
** Pricing / revenue management*
* +  
** Logistics, transportation, airlines, or e-commerce industries*
* +  
** Proven track record of:*
* +  
** Deploying predictive models in production*
* +  
** Driving measurable business impact (revenue growth, margin improvement, retention)*
* +  
** Experience working with commercial or pricing teams is highly desirable**