Data Scientist - Pricing Strategy

Job Description

Job Summary: The Data Scientist - Pricing Strategy plays a key role in driving pricing innovation through advanced analytics and statistical modeling. This role blends pricing strategy with data science capabilities to identify margin improvement opportunities, enhance price optimization, and support pricing governance. The ideal candidate brings deep analytical skills, hands-on experience with data tools, and a strong understanding of pricing levers across markets and customer segments. Essential Functions: 1. Advanced Pricing Analytics & Modeling - Build and maintain statistical models and machine learning algorithms to optimize pricing and discount strategies. - Conduct pricing elasticity studies and scenario analyses using historical data. 2. Market and Customer Segmentation - Analyze customer, product, and transactional data to develop pricing segmentation models. - Identify trends and patterns in client willingness to pay (WTP), profitability, and behavior. 3. Tool & Dashboard Development - Build and automate pricing dashboards in Power BI, Excel, and/or Python. - Create dynamic, user-friendly reporting tools to support sales, finance, and executive teams. 4. Data Management & Integration - Work with large datasets from multiple sources (Salesforce, CPQ, ERP, financial systems) and integrate for pricing analysis. - Develop and maintain a centralized pricing database to track realized pricing and margin performance. 5. Collaboration & Stakeholder Support - Partner with Sales, Product, Finance, and IT to align pricing strategy with business objectives. - Translate complex analytical findings into actionable pricing recommendations and visual narratives. 6. Governance & Strategy - Support development of pricing policies, discount guardrails, and escalation frameworks. - Contribute to quarterly pricing reviews and long-term pricing roadmap. Required Knowledge, Skills, and Abilities: - 3-5 years of experience in pricing analytics, data science, or related field. - Strong background in statistical modeling, regression analysis, and data mining. - Proficient in Python, R, SQL/MySQL, and Excel. - Experience with BI tools (e.g., Power BI, Tableau) and Salesforce data environments. - Strong communication skills with ability to explain data-driven insights to non-technical stakeholders. - Knowledge of pricing principles, margin analysis, and customer segmentation frameworks.