Bhargav Sai Ratnala profile photo 1 on Tal

Bhargav Sai Ratnala

Assistant Manager @ Flipkart | I bridge the gap between business strategy & the tech teams building our marketplace engines. (Product Strategy • Pricing Automation • Risk Mitigation)

Andhra Pradesh

6+ years of work experience

Flipkart
Mar 20251 yr 7 mosPresent

Bengaluru, Karnataka, India

I bridge the gap between high-level business goals and technical execution, owning the strategic direction of end-to-end pricing portfolios at granular category and city levels. I partner directly with core Product, Engineering, and Data Science squads to turn complex business constraints into smart marketplace capabilities. Product Strategy & Feature Design Impact: Xtra Super Saver Launch: Led the entire pricing design for the high-volume grocery track from scratch—taking it from the initial planning stages all the way to a live launch on the Flipkart marketplace. Core Feature Engineering: Partnered closely with core Product teams to define, design, and ship live marketplace capabilities directly into the ecosystem, including Virtual Combos and WoW Pricing Tagging logic. Pricing Automation Engine: Led product requirements and logic translation to fully automate end-to-end pricing workflows for the quick-commerce (minutes grocery) platform, drastically reducing operational latency and scaling real-time dynamic pricing updates. Search & Discovery Optimization: Partnered with engineering teams to optimize the electronics search engine algorithm; designed targeted fallback mechanisms for "nullified searches" ($n=X$) to eliminate zero-result drops, improve discoverability, and recover leaking revenue. Intelligent Pricing Module: Co-owning product discovery and roadmap execution for an intelligent, ML-driven pricing engine to build automated margin-optimization and demand-elasticity logic. Business Operations & Portfolio Growth Impact: Portfolio Strategy: Managed the end-to-end execution of competitive pricing portfolios at granular city and category levels to balance market-level platform margins with consumer value. Monetization & Spend Optimization: Conceptualized and built a discount-based pricing calendar powered by heavy historical sales datasets to effectively map, track, and optimize monetization returns against active promotional spend.
Flipkart
Dec 20231 yr 4 mosMar 2025

Bengaluru, Karnataka, India

Promoted to lead the deployment and guardrails of our core pricing frameworks. My focus shifted from day-to-day data tasks to stabilizing competitive marketplace strategies, piloting innovative promotional structures, and ensuring strict profitability metrics across categories. Key Impact Areas: Promotional Framework Testing: Spearheaded the testing and operational deployment of new, experimental offer types across target categories, monitoring customer adoption and setting up technical guardrails to prevent margin leakage. Dynamic Modeling & Margin Guardrails: Implemented automated, competition-based dynamic pricing models and managed profitability algorithms (NLC+X) to maintain strict platform margin guardrails and market competitiveness. Stakeholder Alignment: Acted as the core operational bridge between category business teams and technical engineering teams to translate promotional business requirements and constraints into working marketplace logic. Workflow Optimization: Scaled complex pricing rule execution, driving framework adoption and offer scalability across fast-moving consumer tracks.
Flipkart
Dec 20212 yrs 1 moDec 2023

Bangalore Urban, Karnataka, India

Stepped into the pricing vertical to solve immediate operational bottlenecks through heavy data modeling and technical automation. My objective was to eliminate manual overhead, optimize data pipelines, and deploy promotional structures that directly drive marketplace revenue. Key Impact Areas: Revenue-Driving Promotions: Handled the data mapping and execution frameworks for high-impact promotional constructs—including combo offers, basket discounts, and ratchet pricing offers—designed to boost cross-selling and increase average order value. Process Automation: Wrote and deployed custom Python scripts to fully automate high-volume daily operational tasks and history-tracking reporting metrics. Manual Overhead Elimination: Successfully eliminated massive manual data processing workloads, building clean automated trackers that saved critical team bandwidth. Data Analysis: Handled deep-dive data extraction and modeling of heavy sales and competitive datasets to feed into upcoming pricing experiments and promotional ROI trackers.
Randstad
Jul 20171 yr 4 mosOct 2018

Bengaluru, Karnataka, India

Client: IBM – Dow Chemical & Pearson Managed end-to-end vendor negotiation tracks and optimized supply chain metrics for major global enterprise clients. Key Impact Areas: Digitized operations contracts directly into SAP systems while maintaining strict SLA compliance. Monitored transit, freight, and transport analytics inside Oracle Transport Management (OTM) to maximize routing efficiency. Compiled daily and weekly QA and analytical performance reports for stakeholders.

Bhargav’s AI Stack

claude code
claude code
gemini
gemini
meta
meta
openai
openai
ChatGPT
ChatGPT
ChatGPT Images
ChatGPT Images

Education

B.Tech, Electronics and communication of engineering

Miracle school of engg

20114 yrs2015

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Headline

Assistant Manager @ Flipkart | I bridge the gap between business strategy & the tech teams building our marketplace engines. (Product Strategy • Pricing Automation • Risk Mitigation)

About

I spend my days figuring out how to take big business goals and turn them into smart, automated systems that run smoothly behind the scenes. Over the last 7+ years at Flipkart, my journey has been all about solving complex backend problems—starting in risk analytics and moving into the core logic that powers our marketplace pricing and search engines. Right now, my work comes down to two main things: 1. Product Operations & Strategy: I act as the translator between our business teams and tech teams. I work closely with engineers, data scientists, and product managers to map out product requirements, automate pricing pipelines, and fix tricky search discovery issues that get in the way of sales. 2. Risk & Analytics: Earlier in my career, I focused heavily on protecting platform revenue. By digging into user data and reseller behavior to uncover fraud patterns, my team and I managed to cut platform financial losses by 25%. I genuinely enjoy fast-paced environments where I can roll up my sleeves with Python or SQL to eliminate messy, manual processes and build scalable platform features instead. 🔹 What I bring to the table: Product Strategy & Lifecycle, Pricing Automation Engines, Search & Discovery Logic, Portfolio Management, and Fraud Risk Mitigation.

Location

Andhra Pradesh

AI stack

claude code

gemini

meta

openai

ChatGPT

ChatGPT Images

Work experience

Assistant Manager – Business Product Management (Flipkart Minutes & Grocery) at Flipkart, Mar 2025 - Present · 1 yr 7 mos, Bengaluru, Karnataka, India, I bridge the gap between high-level business goals and technical execution, owning the strategic direction of end-to-end pricing portfolios at granular category and city levels. I partner directly with core Product, Engineering, and Data Science squads to turn complex business constraints into smart marketplace capabilities. Product Strategy & Feature Design Impact: Xtra Super Saver Launch: Led the entire pricing design for the high-volume grocery track from scratch—taking it from the initial planning stages all the way to a live launch on the Flipkart marketplace. Core Feature Engineering: Partnered closely with core Product teams to define, design, and ship live marketplace capabilities directly into the ecosystem, including Virtual Combos and WoW Pricing Tagging logic. Pricing Automation Engine: Led product requirements and logic translation to fully automate end-to-end pricing workflows for the quick-commerce (minutes grocery) platform, drastically reducing operational latency and scaling real-time dynamic pricing updates. Search & Discovery Optimization: Partnered with engineering teams to optimize the electronics search engine algorithm; designed targeted fallback mechanisms for "nullified searches" ($n=X$) to eliminate zero-result drops, improve discoverability, and recover leaking revenue. Intelligent Pricing Module: Co-owning product discovery and roadmap execution for an intelligent, ML-driven pricing engine to build automated margin-optimization and demand-elasticity logic. Business Operations & Portfolio Growth Impact: Portfolio Strategy: Managed the end-to-end execution of competitive pricing portfolios at granular city and category levels to balance market-level platform margins with consumer value. Monetization & Spend Optimization: Conceptualized and built a discount-based pricing calendar powered by heavy historical sales datasets to effectively map, track, and optimize monetization returns against active promotional spend.

Team Lead – Pricing Operations at Flipkart, Dec 2023 - Mar 2025 · 1 yr 4 mos, Bengaluru, Karnataka, India, Promoted to lead the deployment and guardrails of our core pricing frameworks. My focus shifted from day-to-day data tasks to stabilizing competitive marketplace strategies, piloting innovative promotional structures, and ensuring strict profitability metrics across categories. Key Impact Areas: Promotional Framework Testing: Spearheaded the testing and operational deployment of new, experimental offer types across target categories, monitoring customer adoption and setting up technical guardrails to prevent margin leakage. Dynamic Modeling & Margin Guardrails: Implemented automated, competition-based dynamic pricing models and managed profitability algorithms (NLC+X) to maintain strict platform margin guardrails and market competitiveness. Stakeholder Alignment: Acted as the core operational bridge between category business teams and technical engineering teams to translate promotional business requirements and constraints into working marketplace logic. Workflow Optimization: Scaled complex pricing rule execution, driving framework adoption and offer scalability across fast-moving consumer tracks.

Senior Analyst – Pricing Analytics & Operations at Flipkart, Dec 2021 - Dec 2023 · 2 yrs 1 mo, Bangalore Urban, Karnataka, India, Stepped into the pricing vertical to solve immediate operational bottlenecks through heavy data modeling and technical automation. My objective was to eliminate manual overhead, optimize data pipelines, and deploy promotional structures that directly drive marketplace revenue. Key Impact Areas: Revenue-Driving Promotions: Handled the data mapping and execution frameworks for high-impact promotional constructs—including combo offers, basket discounts, and ratchet pricing offers—designed to boost cross-selling and increase average order value. Process Automation: Wrote and deployed custom Python scripts to fully automate high-volume daily operational tasks and history-tracking reporting metrics. Manual Overhead Elimination: Successfully eliminated massive manual data processing workloads, building clean automated trackers that saved critical team bandwidth. Data Analysis: Handled deep-dive data extraction and modeling of heavy sales and competitive datasets to feed into upcoming pricing experiments and promotional ROI trackers.

Procurement Operations & Supply Chain Analyst at Randstad, Jul 2017 - Oct 2018 · 1 yr 4 mos, Bengaluru, Karnataka, India, Client: IBM – Dow Chemical & Pearson Managed end-to-end vendor negotiation tracks and optimized supply chain metrics for major global enterprise clients. Key Impact Areas: Digitized operations contracts directly into SAP systems while maintaining strict SLA compliance. Monitored transit, freight, and transport analytics inside Oracle Transport Management (OTM) to maximize routing efficiency. Compiled daily and weekly QA and analytical performance reports for stakeholders.

Education

B.Tech, Electronics and communication of engineering, Miracle school of engg