Role Summary
The Pricing Analyst is a critical contributor to a high-growth retail pricing organization, responsible for owning, operating, and continuously improving the price optimization software ecosystem while delivering commercial insights that drive margin improvement, competitive positioning, and revenue growth across channels and geographies. This role blends deep quantitative skill with strategic commercial judgment and cross-functional stakeholder influence : sitting at the intersection of data science, finance, and category strategy. The ideal candidate brings hands-on experience with enterprise pricing platforms (e.g., Revionics, Relex, Impact Analytics, QuickLizard, Pricen, Competera, DemandTec, BlueYonder, TCS Optumera, Yieldigo, 7Learnings, RetailGrid, Mc Kinsey Periscope, ClearDemand ), strong SQL and analytics capability, and the ability to translate optimization outputs into clear pricing recommendations that buying, finance, and commercial teams can act on.
Key Responsibilities
1. Price Optimization Platform Ownership
● Own end-to-end operation of the central price optimization software (e.g Revionics, Relex, Impact Analytics, QuickLizard, Pricen, Competera, DemandTec, BlueYonder, TCS Optumera, Yieldigo, 7Learnings, RetailGrid, Mc Kinsey Periscope, ClearDemand ), including creation and maintenance of price plans, business rules, elasticity inputs, scenario analysis, optimization objectives: Be the Super user for the pricing tool.
● Conduct regular audits of optimization model outputs; identify anomalies, data gaps, or model drift, and recalibrate parameters in response to market and seasonal changes.
● Configure and maintain zone-based, channel-specific, and SKU-level pricing structures across offline and online channels, ensuring omnichannel price consistency where required.
● Manage integration of the pricing tool with competitor intelligence feeds, ERP systems (e.g., SAP/Vistex), and BI platforms — partnering with data engineering teams to ensure clean, complete data flows.
2. Data Analysis, Pricing Scenario Modelling & Commercial Execution
● Design and analyse A/B pricing experiments and test-and-control frameworks to measure the causal impact of price interventions on volume, revenue, and margin — and translate findings into iterative refinements.
● Perform price sensitivity and cross-elasticity analysis at the category, subcategory, and SKU level to identify opportunities for range restructuring and price architecture optimization.
● Support development and execution of pricing strategies across everyday pricing, promotions, markdowns, clearance, and new product introductions (NPI).
● Partner with Category, Finance, and Commercial Operations teams to operationalize pricing decisions, maintain guardrails, and ensure adherence to centralized governance rules.
3. Reporting, Documentation, Training & Stakeholder Communication
● Produce regular pricing performance dashboards monthly covering price index vs. competitors, margin realization, optimization adoption rates, and KPI tracking.
● Prepare executive-level presentations that synthesize pricing insights, highlight risks and opportunities, and communicate clear recommendations to senior leadership. Track and report on the commercial impact of pricing actions taken, feeding learnings back into the optimization model and pricing strategy.
● Document pricing SOPs, system configurations, pricing rules, regional pricing rule differences, and model assumptions to enable knowledge transfer, onboarding, and audit readiness.
● Create end user training materials, and train regional teams on the pricing tools, pricing methodology, and CI platforms.
● Act as a point of escalation and SME for pricing tool queries across the business; liaise with vendor support teams on technical issues as needed.
Qualifications & Requirements
Education and Experience
● Bachelor's degree (required) in Finance, Business Analytics, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field. Master's degree or MBA is advantageous.
● Hands-on experience operating, configuring, or administering a price optimization platform (e.g Revionics, Relex, Impact Analytics, QuickLizard, Pricen, Competera, DemandTec, BlueYonder, TCS Optumera, Yieldigo, 7Learnings, RetailGrid, Mc Kinsey Periscope, ClearDemand ); candidates with adjacent tool experience and strong aptitude to learn are also considered.
● 6 -10 years of experience in pricing analysis, revenue optimization, commercial analytics, or a related field with a demonstrable exposure to the end-to-end pricing lifecycle.
● Professional certifications in pricing (e.g., Certified Pricing Professional – CPP), data analytics, or revenue management.
● Prior experience in retail, FMCG, consumer goods, or omnichannel e-commerce environments is strongly preferred.
● Track record of using pricing data to influence commercial decisions and drive measurable margin or revenue outcomes.
Technical Skills
● Pricing & Optimization Software: Worked on Revionics, Relex, Impact Analytics, QuickLizard, Pricen, Competera, DemandTec, BlueYonder, TCS Optumera, Yieldigo, 7Learnings, RetailGrid, Mc Kinsey Periscope, ClearDemand .
● Advanced Excel (required): Complex formulas, PivotTables, scenario modelling, and financial models.
● SQL (strongly preferred): ability to write and optimize queries for data extraction, transformation, and analysis from relational databases (e.g., Snowflake, BigQuery, SQL Server, Teradata).
● Python or R (advantageous): experience with pandas, NumPy, or statistical/ML libraries for demand modelling, elasticity analysis, or pricing automation is a significant differentiator.
Other Skills
● Strong quantitative and problem-solving ability with high attention to precision and data integrity.
● Demonstrated ability to build pricing and elasticity models, design A/B pricing experiments
● Commercial instinct: capable of connecting analytical findings to business strategy and communicating the 'so what' clearly to non-technical audiences.
● Understanding of core pricing methodologies including cost-plus, value-based, competitive, dynamic, and psychological pricing principles.
● Collaborative mindset with a genuine desire to build pricing capability in
