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Ayushi Verma

Ayushi Verma

Lead Analytics & Data Products | Pricing, Promotions & Retail Intelligence

Talent
BengaluruMember since April 16, 2026
SQLHadoopTeradataSnowflakeBigQueryPythonRPower BITableauLookerFigmaElasticity ModellingMarket Basket AnalysisCustomer SegmentationRegression
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About

Analytics Lead with 6+ years of deep expertise in SQL-heavy data architecture, statistical modelling, and the design of scalable analytical products. As the founding analyst for Lowe's Pro Intel team, I built the team's entire data infrastructure from scratch — delivering platforms, dashboards, and pricing models that now drive operational and strategic decisions across a $30B business. I combine strong technical depth (SQL, Python, BI tools) with business acumen, consistently translating complex data into clear, high-impact insights for senior stakeholders.

Experience

Lead Analyst — Pro Intel at Lowe's Services India (2025-03 – Present)

Primary analytics lead for Pro Intel, partnering with Product Managers and cross-functional leads to drive data strategy and prioritisation. Built entire data infrastructure and reporting frameworks for bulk performance metrics and pricing optimization.

  • Act as the primary analytics lead for Pro Intel — partnering with Product Managers and cross-functional leads to drive data strategy and prioritisation.
  • Architected the Bulk Analytical Dataset (ADS) — a centralised reporting solution for evergreen bulk performance metrics, enabling pricing managers to simulate, add, and remove bulk promotional offers.
  • Innovated business measurement by introducing the "Sold Quote Close Rate" metric — a non-deflated conversion measure that filters out abandoned quotes for a more accurate view of true close performance.
  • Led comprehensive competitive intelligence analysis against a major competitor; identified key offer gaps and recommended strategic pricing updates projected to improve sales by at least $2.7M per month.
  • Conceptualised and built the Quote ADS and performance reporting to optimise the Pro customer segment (~33% of total company sales).
  • Conducted exploratory data analysis to identify margin-leakage: uncovered staggered sales exploitation where customers manipulated quote sizes to trigger Pro discounts.
  • Mentor a team of two (Senior Analyst + Analyst), overseeing work distribution and analytical frameworks.

Senior Analyst — Online Pricing, Price Lab & Pro Intel at Lowe's Services India (2021-01 – 2025-02)

Rotated across three teams as sole analytics resource, independently building all data infrastructure, dashboards, and reporting frameworks. Built 20+ analytical dashboards serving as primary decision-support layer for pricing managers.

  • Rotated across three teams (Online Pricing, Price Lab, Pro Intel) as the sole analytics resource in each — independently building all data infrastructure, dashboards, and reporting frameworks from scratch for every business function.
  • Built 20+ analytical dashboards across three business functions, serving as the primary decision-support layer for pricing managers evaluating national price rollouts and competitor-following actions.
  • Measured A/B price test outcomes within the Price Lab team — analysis saved $10M in annual margin and generated $3M in incremental revenue within the Home Decor category.
  • Designed and built high-impact reporting suites including "Price Visibility" and "Top OKR Tracking for Pricing & Promotion" — replacing manual processes and providing real-time metric visibility to leadership.
  • Produced an end-to-end Power BI report tracking the complete lifecycle of price changes at Lowe's — from initial system entry through in-store activation — providing visibility previously unavailable to the business.
  • Quantified financial impact of price changes driven by different business reasons; modelled forward-looking impact of planned changes.

Analyst — Online Pricing (DACI) at Lowe's Services India (2019-06 – 2020-12)

Calculated price elasticity of demand across 100K+ items using statistical models and machine learning. Automated elasticity calculation pipeline to reduce model run-time and generate price recommendations.

  • Calculated price elasticity of demand across 100K+ items using statistical models and machine learning in Python.
  • Automated the elasticity calculation pipeline to reduce model run-time and generate price recommendations for prioritised items.

Education

B.A. in Economics (Hons) – Hansraj College, Delhi University

Skills

Lead Analytics & Data ProductsPricingPromotions & Retail Intelligence

Reviews

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