Sohil Sharma profile photo 1 on Tal

Sohil Sharma

Product Leader @ INDmoney

Greater Bengaluru Area

8+ years of work experience

INDmoney
Nov 20259 moPresent

Bengaluru

Leading product for INDcredit, INDmoney's full-stack lending suite (LOS, RMS, Collateral Management System, LMS) built ground-up to power the NBFC. Scaled to Rs. 30 Cr+ in monthly disbursals. - AI Loan Assistant: Launched an LLM-powered conversational assistant handling issue resolution, ticket raising, FAQs, foreclosure, and queries on future instalments end-to-end. Owned intent design, response guardrails, escalation policy, and quality tracking. Cut CX tickets and support dependency by 45% (~Rs. 15L annual savings) and lifted post-disbursal NPS. - ML-Driven Intelligent Offer Generation: Shipped a credit-score-based ML risk-segmentation layer over bureau data that personalises loan amount, interest rate, and tenure per applicant. Partnered with risk on segment thresholds and monitored acceptance-by-band post-launch. Lifted approval rate by 2% and offer-acceptance by 0.8%, delivering ~Rs. 1 Cr in additional monthly disbursals by unlocking safer near-prime cohorts. - Funnel Optimization: Reduced offer-generation drop-offs by 1.5% via RTA fetch-error diagnosis and eligibility-policy revision, driving 4% loan-book growth (~Rs. 1.2 Cr additional monthly disbursals). Designed a smart drop-off recovery widget with auto-redirection to the latest pending step, reducing journey-wide drop-offs by another 2.1% (~Rs. 1.6 Cr).
Asper.ai
Apr 20257 moNov 2025

Bengaluru · Hybrid

AI initiatives - 1. Designed and shipped a multi-agent system for autonomous enterprise demand planning. Flow: a Retrieval agent pulls context via RAG, a Scenario agent proposes the what-if futures worth testing (supply shocks, competitor moves, festive spikes), a Simulation agent computes each scenario across pricing, budget, and inventory, a Critic agent sanity-checks outputs against historical patterns and business rules, and an Orchestrator routes between agents and decides when the answer is complete. ML initiatives - 1. Built an ML-Powered Strategy Simulator which increased the average forecast accuracy by 23% and reduced forecast consensus planning time from 4-6 hours to just 30 minutes across industries.
Asper.ai
Apr 202411 moMar 2025

Bengaluru · Hybrid

Increased Adoption via Demand planning workflow completion 1. Boosted demand planning workflow completion and session-to-decision conversion from 53% to 78% by transforming user experience through data-driven insights, streamlined navigation, and modernising demand planning workflows. Customer On-boarding and Support revamp 1. Reduced support burden by 85%, cutting navigation-related tickets and onboarding time by 62%
Gojek
Apr 20213 yApr 2024

Bengaluru

Revenue Growth and Customer Satisfaction - Supply Availability Optimization: 1. Reduced customer wait times by 20% (4.2 to 3.2 mins) and improved booking success rate from 87% to 94% (supported by statistically significant A/B tests) through an intelligent driver positioning system leveraging spatio-temporal algorithms, predictive demand modelling, and real-time driver redistribution. 2. Driver idle time reduced by 23% via optimized supply positioning and incentive allocation frameworks, providing a win-win situation for both drivers and customers. 3. Designed, deployed and evaluated experiments to measure the incremental effect due to the launch of ML based product features using A/B tests, switchback experiments with statically significant results
Myntra
May 20201 yr 5 mosSep 2021

Bengaluru, Karnataka, India

1. Built a demand estimation framework which helped the inventory planning team to optimize their budget and warehouse capacity for the upcoming seasons of 2021 and 2022. 2. Helped with the launch and provided analytics support to the social E-commerce charter which is the first of its kind in India. Helped derive multiple insights and built the entire reporting structure from scratch
Mu Sigma Inc.
Jan 20182 y 4 moMay 2020

Bangalore

Client: LEADING CPG MANUFACTURER Team: STRATEGIC REVENUE MANAGEMENT - U.S :- 1. Worked on a $2M engagement, collaborating Analytics, Trade Management and Revenue Growth 2. Built a Sales Attribution white box model (Stepwise linear regression with VIF checks and Beta correction) leveraging multiple factors like pricing, market competitors & external factors, supported by R libraries 3. Enabled the business to measure the incremental effect of in-store promotions by devising a Baseline sales success criteria 4. Reduced 1000+ hours of manual effort for Account Managers by developing Competitor Clash Avoidance and the Pricing views of Trade Promotion Management (TPM) tool which help the Account Managers design promo plans in accordance to the forecasted competitor prices, for a better pricing negotiation and a win-win deal with Retailers 5. Developed a co-promotion recommendation system which provides insights on possible product bundling combinations using Market Basket analysis on transaction level historical sales data, leveraging Apriori Association rules Team: GLOBAL SOURCING AND LOGISTICS - U.K :- Brought in visibility into potential savings of £1.5M by developing and automating data driven supplier selection scenarios in the form of a Power BI dashboard Team: GLOBAL DIGITAL FOUNDATIONS 1. Designed Profit Pools and Cross Border Pricing reporting dashboard for all retailers of the Customer in the Europe region. Defined a value at risk metric to identify products at risk of ~£0.7M due to merger of two retailers. 2. Analysed the synergy effect of advertisements and in-store promotions observing a 30% lift due to coupling of pricing discounts and T.V advertisements using Interaction modelling

Sohil’s AI Stack

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langchain
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lovable
mcp
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Education

Manipal institute of technology

Bachelor of Technology (B.Tech.), Electronics and Communications Engineering

Manipal institute of technology

20144 yrs2018
JAI HIND COLLEGE, MUMBAI

JAI HIND COLLEGE, MUMBAI

20122 yrs2014

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Headline

Product Leader @ INDmoney

About

As a Senior Product Manager at INDmoney with nearly a decade of experience, my focus lies in driving impactful product development while leveraging data-driven insights and product management expertise. Currently, I lead the development of INDcredit, a full-stack lending suite that encompasses Loan Origination, Risk, Collateral, and Loan Management Systems.

Location

Greater Bengaluru Area

AI stack

claude code

cursor

langchain

langgraph

lovable

mcp

Work experience

Senior Product Manager at INDmoney, Nov 2025 - Present · 9 mo, Bengaluru, Leading product for INDcredit, INDmoney's full-stack lending suite (LOS, RMS, Collateral Management System, LMS) built ground-up to power the NBFC. Scaled to Rs. 30 Cr+ in monthly disbursals. - AI Loan Assistant: Launched an LLM-powered conversational assistant handling issue resolution, ticket raising, FAQs, foreclosure, and queries on future instalments end-to-end. Owned intent design, response guardrails, escalation policy, and quality tracking. Cut CX tickets and support dependency by 45% (~Rs. 15L annual savings) and lifted post-disbursal NPS. - ML-Driven Intelligent Offer Generation: Shipped a credit-score-based ML risk-segmentation layer over bureau data that personalises loan amount, interest rate, and tenure per applicant. Partnered with risk on segment thresholds and monitored acceptance-by-band post-launch. Lifted approval rate by 2% and offer-acceptance by 0.8%, delivering ~Rs. 1 Cr in additional monthly disbursals by unlocking safer near-prime cohorts. - Funnel Optimization: Reduced offer-generation drop-offs by 1.5% via RTA fetch-error diagnosis and eligibility-policy revision, driving 4% loan-book growth (~Rs. 1.2 Cr additional monthly disbursals). Designed a smart drop-off recovery widget with auto-redirection to the latest pending step, reducing journey-wide drop-offs by another 2.1% (~Rs. 1.6 Cr).

Senior AI Product Manager at Asper.ai, Apr 2025 - Nov 2025 · 7 mo, Bengaluru · Hybrid, AI initiatives - 1. Designed and shipped a multi-agent system for autonomous enterprise demand planning. Flow: a Retrieval agent pulls context via RAG, a Scenario agent proposes the what-if futures worth testing (supply shocks, competitor moves, festive spikes), a Simulation agent computes each scenario across pricing, budget, and inventory, a Critic agent sanity-checks outputs against historical patterns and business rules, and an Orchestrator routes between agents and decides when the answer is complete. ML initiatives - 1. Built an ML-Powered Strategy Simulator which increased the average forecast accuracy by 23% and reduced forecast consensus planning time from 4-6 hours to just 30 minutes across industries.

AI Product Manager at Asper.ai, Apr 2024 - Mar 2025 · 11 mo, Bengaluru · Hybrid, Increased Adoption via Demand planning workflow completion 1. Boosted demand planning workflow completion and session-to-decision conversion from 53% to 78% by transforming user experience through data-driven insights, streamlined navigation, and modernising demand planning workflows. Customer On-boarding and Support revamp 1. Reduced support burden by 85%, cutting navigation-related tickets and onboarding time by 62%

Technical Product Manager at Gojek, Apr 2021 - Apr 2024 · 3 y, Bengaluru, Revenue Growth and Customer Satisfaction - Supply Availability Optimization: 1. Reduced customer wait times by 20% (4.2 to 3.2 mins) and improved booking success rate from 87% to 94% (supported by statistically significant A/B tests) through an intelligent driver positioning system leveraging spatio-temporal algorithms, predictive demand modelling, and real-time driver redistribution. 2. Driver idle time reduced by 23% via optimized supply positioning and incentive allocation frameworks, providing a win-win situation for both drivers and customers. 3. Designed, deployed and evaluated experiments to measure the incremental effect due to the launch of ML based product features using A/B tests, switchback experiments with statically significant results

Senior Product Analyst at Myntra, May 2020 - Sep 2021 · 1 yr 5 mos, Bengaluru, Karnataka, India, 1. Built a demand estimation framework which helped the inventory planning team to optimize their budget and warehouse capacity for the upcoming seasons of 2021 and 2022. 2. Helped with the launch and provided analytics support to the social E-commerce charter which is the first of its kind in India. Helped derive multiple insights and built the entire reporting structure from scratch

Decision Scientist at Mu Sigma Inc., Jan 2018 - May 2020 · 2 y 4 mo, Bangalore, Client: LEADING CPG MANUFACTURER Team: STRATEGIC REVENUE MANAGEMENT - U.S :- 1. Worked on a $2M engagement, collaborating Analytics, Trade Management and Revenue Growth 2. Built a Sales Attribution white box model (Stepwise linear regression with VIF checks and Beta correction) leveraging multiple factors like pricing, market competitors & external factors, supported by R libraries 3. Enabled the business to measure the incremental effect of in-store promotions by devising a Baseline sales success criteria 4. Reduced 1000+ hours of manual effort for Account Managers by developing Competitor Clash Avoidance and the Pricing views of Trade Promotion Management (TPM) tool which help the Account Managers design promo plans in accordance to the forecasted competitor prices, for a better pricing negotiation and a win-win deal with Retailers 5. Developed a co-promotion recommendation system which provides insights on possible product bundling combinations using Market Basket analysis on transaction level historical sales data, leveraging Apriori Association rules Team: GLOBAL SOURCING AND LOGISTICS - U.K :- Brought in visibility into potential savings of £1.5M by developing and automating data driven supplier selection scenarios in the form of a Power BI dashboard Team: GLOBAL DIGITAL FOUNDATIONS 1. Designed Profit Pools and Cross Border Pricing reporting dashboard for all retailers of the Customer in the Europe region. Defined a value at risk metric to identify products at risk of ~£0.7M due to merger of two retailers. 2. Analysed the synergy effect of advertisements and in-store promotions observing a 30% lift due to coupling of pricing discounts and T.V advertisements using Interaction modelling

Education

Bachelor of Technology (B.Tech.), Electronics and Communications Engineering, Manipal institute of technology

JAI HIND COLLEGE, MUMBAI