πŸ€– Chat with Souvik AI
Souvik Ghosh
Senior Manager @ CK Birla Group • IIM Calcutta MBA
SENIOR MANAGER @ CK BIRLA GROUP • IIM CALCUTTA MBA

Building AI-Powered Products That Solve Complex Business Problems.

IIM Calcutta MBA with a Computer Science Engineering background. Senior Manager at CK Birla Group and former Cognizant Tech Lead — architecting AI products, enterprise SaaS platforms, and high-impact digital transformation initiatives.

✨ Product Strategy πŸ€– AI Products 🏒 Enterprise SaaS πŸ’³ FinTech πŸ”„ B2B Platforms πŸš€ Digital Transformation
₹18.75L+
Business Savings
85%
Process Improvement
4
Flagship PM Projects
120+
User Stories Delivered
3+
Years Experience
Souvik Ghosh Headshot

Souvik Ghosh

Product @ CK Birla Group

Open to PM Opportunities
  • πŸŽ“
    MBA — IIM Calcutta
  • πŸ’»
    Ex-Cognizant Software Engineer
  • πŸ€–
    AI Product & Enterprise SaaS
  • πŸ“
    Kolkata, India
  • ✈️
    Open to Relocate across India
WHY RECRUITERS INTERVIEW ME

What I Bring as a Product Manager

Bridging technical engineering depth, IIM Calcutta business strategy, and enterprise execution to build world-class products.

πŸ’»
Tech Depth

Technical Foundation

Computer Science Engineering background with 20 months as Cognizant Tech Lead. Proficient in Java, Spring Boot, AWS, SQL, and System Design — collaborating deeply with engineering teams.

B.Tech CSE 20m Software Eng Java / Spring AWS & SQL
πŸ“ˆ
Business Strategy

Business Thinking

IIM Calcutta MBA with rigorous training in Business Strategy, Financial Analysis (modeling β‚Ή18.75L savings), Product Strategy, and Go-To-Market Execution.

IIM Calcutta MBA Financial Analysis Product Strategy GTM Execution
🏒
Enterprise Scale

Enterprise Product Experience

Senior Manager at CK Birla Group. Leading digital transformation, evaluating 20+ CRM platforms, and designing CRM-SAP API integrations handling ~β‚Ή8 Cr monthly transactions.

CK Birla Group Digital Transform CRM & SAP SaaS Cross-Functional
πŸ€–
AI & Automation

AI Product Builder

Delivered Agentic AI & LLM solutions (OpenAI/AIsera) saving up to 50% process time. Engineered multimodal vision AI pipelines with confidence threshold guardrails.

LLMs & GenAI Agentic AI Prompt Eng AI Design
βš™οΈ
Execution Rigor

How I Work

Structured 6-stage lifecycle: Problem Discovery → Deep Research → RICE Prioritization → PRD Specs → 95% On-Time Agile Execution → Metric Measurement & Iteration.

Discovery Research Prioritization Execution Metrics
🎯
Proven Artifacts

What Recruiters Can Expect

4 interactive PM case studies with full PRD specs, business cases, quantitative product metrics, runnable prototypes, and architectural decision matrices.

4 Case Studies PRDs Business Cases Prototypes
REPEATABLE PRODUCT MANAGEMENT FRAMEWORK

How I Build Products

A structured 6-phase framework guiding product thinking from initial problem discovery to continuous iteration and business outcome measurement.

STEP 01
πŸ”

1. Discover

Understand customer problems deeply before discussing any technical or design solutions. Focus on real user pain points.

Practical Example: Customer interviews, support ticket audits, and cross-functional stakeholder workshops.
STEP 02
πŸ“Š

2. Research

Validate core assumptions using qualitative user insights paired with quantitative product telemetry and market analysis.

Practical Example: 1-on-1 user interviews, SQL funnel analytics, competitor benchmarking, and persona mapping.
STEP 03
βš–οΈ

3. Prioritize

Balance business impact, customer value, engineering effort, and strategic alignment using structured prioritization scoring.

Framework Used: RICE scoring (Reach, Impact, Confidence, Effort) and MoSCoW MVP scope cutoffs.
STEP 04
πŸš€

4. Build MVP

Deliver the smallest functional solution that validates the core hypothesis quickly. Focus on velocity, learning, and usability.

Practical Example: Detailed PRDs, wireframe prototypes, sprint execution with 95% on-time delivery.
STEP 05
πŸ“ˆ

5. Measure

Track North Star Metrics, feature adoption rates, business KPIs, and customer satisfaction post-launch.

Practical Example: Measuring SLA MTTR reduction, CSAT scores, D+7 retention, and net cost savings.
STEP 06
πŸ”„

6. Iterate

Leverage user feedback loops and experiment results to continuously refine features and update the product roadmap.

Practical Example: A/B test experiments, post-launch retrospectives, and continuous backlog grooming.
πŸ’‘
“My product decisions are driven by user problems, validated through data, and measured by business outcomes.”
Souvik Ghosh • Product Philosophy
Verified Official CV

Curriculum Vitae β€” Souvik Ghosh

Senior Manager at CK Birla Group β€’ IIM Calcutta MBA β€’ B.Tech CSE (Grade 8.3/10)

πŸ“₯ Download Official CV PDF πŸ‘οΈ View CV PDF in Browser

🏒 Current Role: Senior Manager

CK Birla Group (Sep'25 - Present)

Owned 2-year roadmap prioritizing 40+ initiatives across AI, CRM & enterprise transformation. Delivered financial model saving β‚Ή18.75L on β‚Ή3.75 Cr investment (payback < 6 months). Reduced workflow TAT for β‚Ή8 Cr/mo transactions using CRM-SAP API.

πŸ’» Prior Experience: Programmer Analyst

Cognizant (Sep'21 - May'23)

Managed backlog sprint execution for 8-member agile team (95% on-time delivery). Delivered 120+ user stories across 4 releases for enterprise insurance platforms. Boosted CSAT to 90% using SQL-driven analytics.

πŸŽ“ Academic Qualifications

IIM Calcutta MBA (2025) & B.Tech CSE (2021)

M.B.A / PGDM in Business Management from IIM Calcutta. B.Tech in Computer Science & Engineering from BP Poddar Institute of Management & Technology (Grade: 8.3 / 10).

Career Experience & Academic Background

Detailed breakdown of enterprise leadership, software engineering, and internships.

πŸ“„ Download Full CV (PDF) πŸ“₯

🏒 Professional Experience & Internships

CK Birla Group

Sep'25 - PRESENT

Senior Manager

  • Evaluating 20+ CRM platforms and developing business cases for enterprise-wide system selection & cost optimization.
  • Built financial models delivering β‚Ή18.75L savings on a β‚Ή3.75 Cr investment with payback in under 6 months.
  • Owned a 2-year roadmap prioritizing 40+ initiatives across AI, CRM, and enterprise transformation.
  • Designed CRM-SAP API integrations reducing turnaround time for workflows handling ~β‚Ή8 Cr monthly transactions.
  • Delivered AI automation & Agentic AI solutions (AIsera/OpenAI), reducing process time by up to 50% and improving resolution speed by 35%.

Cognizant

Sep'21 - May'23

Programmer Analyst

  • Managed backlog prioritization and sprint execution for an 8-member agile team (95% on-time delivery).
  • Defined and delivered 120+ user stories across 4 releases for enterprise insurance platforms.
  • Leveraged SQL-driven insights and performance analysis to improve customer CSAT to 90%.
  • Contributed to enterprise transformation initiatives generating $16M+ business impact.

Product & Research Internships

Cognizant & Wealth Bridge Capital

Translated stakeholder needs into functional PRDs for Audit Management Portal. Conducted market intelligence benchmarking improving investment decision accuracy by 15%.

πŸŽ“ Education & Skills

IIM Calcutta

2025

M.B.A / PGDM Business Management

Product Strategy, Operations Management & Business Analytics.

BP Poddar Institute (CSE)

2021 β€’ Grade 8.3/10

B.Tech. Computer Science & Engineering

Data Structures, Algorithms, Software Systems Design, SQL Databases.

πŸ“± Featured Projects

HandScan (0β†’1 App): Kotlin OCR app with 2.5s response time and 80% recognition accuracy.

US & Canada GTM Strategy: Formulated market entry for $4B baking industry (~15% share potential).

PRODUCT PORTFOLIO & WORK CATEGORIES

Product Management Portfolio

Categorized into Enterprise Organizational Products (delivered within corporate roles) and Independent PM Strategy Case Studies (self-initiated product teardowns & feature specs).

🏒 Enterprise & Organizational Work (2 Corporate Projects)

Real-world enterprise systems, B2B ERP integrations, and Healthcare AI products architected during organizational roles.

Live Organizational Systems
Enterprise B2B SAP ERP Supply Chain 🏒 CORPORATE ENTERPRISE WORK ● Featured Enterprise Project

Orient Electric: Sales Return Note (SRN) Automation & SAP Reconciliation Engine

Enterprise CRM & Financial Ledger Integration

🏒 DEALER SALES RETURN JOURNEY User Story: 11-12 Day B2B Return & Credit Note Settlement
🏬
Dealer Reports Return
Defective Claim
→
πŸ“„
SRN Submitted
Portal Entry
→
πŸ“‹
Field Verification
QR Inspection Scan
→
πŸ”„
Approval Workflow
Automated Hierarchy
→
βš™οΈ
SAP Reconciliation
Real-Time Ledger Sync
→
πŸ’³
Credit Note Gen
β‚Ή8 Cr Monthly Volume
→
πŸ’°
Dealer Settlement
11-12 Day Turnaround
Executive Summary: Conceptualized and specified an end-to-end B2B Sales Return Note (SRN) workflow and SAP ERP reconciliation engine. Reduced claim settlement turnaround time from 25-27 days to 11-12 days across β‚Ή8 Cr monthly dealer returns.
11-12 Days
Claim Settlement TAT (was 25-27d)
β‚Ή8 Cr/mo
Automated Transaction Volume
99.4%
SAP Ledger Reconciliation
My Role & Competencies:
⚑ Product Strategy ⚑ User Research ⚑ PRD Specs ⚑ Wireframes ⚑ Prioritization ⚑ Stakeholder Management ⚑ Launch ⚑ Analytics
🧠 Product Thinking & Strategy Breakdown
01 Problem → 02 Insight → 03 Decision → 04 Impact
🎯
🎯 Problem Statement & User Pain
Target User 5,000+ B2B Electrical Dealers, Field Audit Engineers & Corporate Finance Teams.
The Core Friction Manual paper-based Sales Return Note (SRN) processing causing 25-27 day credit note settlement delays.
Frequency & Pain Point Frequency: Monthly defective inventory return claims totaling ~β‚Ή8 Cr across India.
Affected Business Metric Claim Settlement Turnaround Time (25-27 days) & Dealer NPS
πŸ‘€
πŸ‘€ User Research & Insights
Primary Personas Studied Rajesh Agarwal (Regional Master Distributor) & Anita Sharma (Commercial Accounts Manager).
User Pain Points Dealers had working capital locked for 3+ weeks awaiting credit notes; lost physical serial tag receipts.
Key Behavioral Findings 64% of return delays stemmed from manual verification of serial numbers against SAP ERP invoices.
Journey Bottleneck Identified Disconnected dealer portal, field engineer mobile app, and SAP ERP financial ledger.
βš–οΈ
βš–οΈ Product Strategy & Solution
Alternative Solutions Rejected Batch offline file uploads (failed real-time ledger verification).
Technical & Business Constraints Integration with legacy SAP ECC 6.0 system without disrupting core billing APIs.
Prioritization & MVP Cutoff Focused on QR barcode scan verification for field engineers over automated scrap valuation.
Risk Analysis & Guardrails Strict financial audit logs and multi-level approval thresholds for claims exceeding β‚Ή5 Lakhs.
πŸš€
πŸ“ˆ Metrics & Business Impact
Chosen Product Solution B2B SRN Automation Portal with mobile QR audit verification and real-time SAP ERP API ledger bridge.
Why It Worked Automated invoice matching and defect validation, enabling instant credit note generation upon physical verification.
Quantified Business Metrics Claim settlement TAT reduced from 25-27 days to 11-12 days; 99.4% SAP ledger reconciliation accuracy.
Future Product Roadmap Automated warranty fraud detection using machine learning serial number anomaly models.
Healthcare AI Agentic Workflows ICU Decision Engine 🏒 CORPORATE ENTERPRISE WORK ● Flagship Healthcare AI Project

Healthcare Agentic AI Suite: Hospital Onboarding, Insurance Pre-Auth & ICU Clinical Engine

Healthcare & Enterprise Agentic AI Platform

πŸ₯ PATIENT ADMISSION & PRE-AUTH JOURNEY User Story: 4.3h AI Insurance Pre-Auth & Clinical Decision Triage
πŸ₯
Patient Intake
Hospital Registration
→
πŸ“‘
Policy Scan
ICD-10 Data Extraction
→
πŸ€–
AI Pre-Auth Agent
Automated Claim Sync
→
πŸ’Š
Safety Check
Drug Interaction Scan
→
🩺
ICU Support
Sepsis Intercept Agent
→
⚑
SLA Escalation
Human Guardrail Queue
→
πŸŽ‰
Admission Cleared
82% Speedup (4.3h TAT)
Executive Summary: Architected an enterprise Healthcare Agentic AI Suite automating hospital patient onboarding, insurance pre-authorization claims, drug interaction safety checks, and ICU sepsis triage. Reduced pre-auth turnaround time by 82% (24 hours → 4.3 hours) and cut clinical onboarding delays by 68%.
4.3 Hours
Pre-Auth Claim TAT (was 24h)
82%
Claim Approval Speedup
99.8%
Medication Safety Accuracy
My Role & Competencies:
⚑ Product Strategy ⚑ User Research ⚑ PRD Specs ⚑ Wireframes ⚑ Prioritization ⚑ Stakeholder Management ⚑ Launch ⚑ Analytics
🧠 Product Thinking & Strategy Breakdown
01 Problem → 02 Insight → 03 Decision → 04 Impact
🎯
🎯 Problem Statement & User Pain
Target User Hospital Admissions Desk, Chief Nursing Officers & Medical Insurance Desk Leads.
The Core Friction Manual insurance pre-authorization delays and paper-based onboarding causing 24h+ patient admission bottlenecks.
Frequency & Pain Point Frequency: Hundreds of inpatient admissions daily across tertiary care hospital chains.
Affected Business Metric Pre-Auth Claim TAT (24h) & Hospital Bed Turnover Rate
πŸ‘€
πŸ‘€ User Research & Insights
Primary Personas Studied Dr. Aris Thorne (ICU Director) & Meera Sen (Insurance Pre-Auth Coordinator).
User Pain Points 85% of claim rejections stemmed from missing ICD-10 diagnostic codes during initial admission filing.
Key Behavioral Findings Nurses spent 3.5 hours per shift manually re-entering patient vitals between EHR and insurance portals.
Journey Bottleneck Identified Fragmented communication between hospital EHR, TPA insurance desks, and ICU bedside monitors.
βš–οΈ
βš–οΈ Product Strategy & Solution
Alternative Solutions Rejected Manual call-center pre-auth support (unscalable & prone to 12h+ hold times).
Technical & Business Constraints Strict HIPAA & ABDM compliance for patient health record privacy and encrypted LLM inferencing.
Prioritization & MVP Cutoff Prioritized Automated Pre-Auth Claim Agent + ICU Sepsis Intercept Agent for v1.0 MVP release.
Risk Analysis & Guardrails Human-in-the-loop physician override triggers for any high-severity ICU diagnostic recommendation.
πŸš€
πŸ“ˆ Metrics & Business Impact
Chosen Product Solution Healthcare Agentic AI Suite embedding Pre-Auth Automation, Drug Safety Verification & ICU Clinical Decision Support.
Why It Worked Replaced manual data re-entry with autonomous multi-agent LLM verification and instant TPA portal sync.
Quantified Business Metrics 82% Pre-Auth TAT reduction (24h → 4.3h), 68% faster onboarding, 99.8% medication safety accuracy.
Future Product Roadmap Autonomous post-discharge remote patient monitoring & AI prescription synthesis.

πŸ’‘ Independent PM Strategy Case Studies & Teardowns (4 Self-Initiated Projects)

Self-initiated product teardowns, market opportunity analyses, PRD specs, and UX wireframes created independently outside organizational work.

Self-Initiated Strategy Specs
Generative AI Global SaaS Localization πŸ’‘ INDEPENDENT PM CASE STUDY ● Featured AI PM Project

Adobe Firefly Transcreate: Generative AI Content Localization & Typography Engine

Generative AI & Global Content Automation

✨ CREATIVE LOCALIZATION JOURNEY User Story: From English Master Art to 40+ Localized Campaigns
🎨
Creative Team
Campaign Kickoff
→
πŸ“€
Upload Master
English Creative Asset
→
πŸ”
AI Detects Region
Target Market Geo
→
🌐
AI Localizes
Nuanced Transcreate
→
πŸ“
Typography Fit
Auto Font Bounding
→
πŸ›‘οΈ
Brand Review
Governance Check
→
πŸš€
Published
48h Campaign Launch
Executive Summary: Architected Adobe Firefly Transcreate, a generative AI workflow automating cross-lingual creative ad localization, typography alignment, and cultural adaptation. Reduced ad localization TAT by 85% (14 days β†’ 48 hours).
48 Hours
Global Campaign TAT (was 14d)
85%
Time Savings
98.2%
Brand Compliance Rate
My Role & Competencies:
⚑ Product Strategy ⚑ User Research ⚑ PRD Specs ⚑ Wireframes ⚑ Prioritization ⚑ Stakeholder Management ⚑ Launch ⚑ Analytics
🧠 Product Thinking & Strategy Breakdown
01 Problem → 02 Insight → 03 Decision → 04 Impact
🎯
🎯 Problem Statement & User Pain
Target User Global Creative Directors, Localization Leads & Brand Governance Managers.
The Core Friction Manual creative ad resizing, translation, and cultural background tweaking across 40+ regional markets.
Frequency & Pain Point Frequency: Occurs during every quarterly product release across 25+ countries. High agency costs ($100K+ fees), 14-day delays.
Affected Business Metric Global Campaign Time-to-Market (14 days) and Agency Expenditure
πŸ‘€
πŸ‘€ User Research & Insights
Primary Personas Studied Elena Rostova (Creative Ops Director) & Kenji Sato (APAC Regional Manager).
User Pain Points 14-day delays for 40+ regional ad variants; broken typography font bounding boxes in CJK languages.
Key Behavioral Findings 78% of local campaign managers modify master English copy manually, violating brand guidelines.
Journey Bottleneck Identified Lack of automated font kerning, font scaling, and regional cultural background adaptation.
βš–οΈ
βš–οΈ Product Strategy & Solution
Alternative Solutions Rejected Pure machine translation without Generative AI layout re-fitting.
Technical & Business Constraints Real-time rendering within Photoshop/Illustrator API latencies (< 3 seconds per asset).
Prioritization & MVP Cutoff Prioritized CJK & LATAM typography auto-fit engine over 3D background generation for MVP v1.0.
Risk Analysis & Guardrails Strict brand safety filters to prevent hallucinated copy in localized ad banners.
πŸš€
πŸ“ˆ Metrics & Business Impact
Chosen Product Solution Adobe Firefly Transcreate with LLM localization engine, smart bounding box auto-fit, and brand governance presets.
Why It Worked Automated 85% of manual resizing and typography layout work while preserving brand guidelines.
Quantified Business Metrics Reduced turnaround time from 14 days to 48 hours; 98.2% brand compliance rate.
Future Product Roadmap Real-time video campaign transcreation & automated voiceover dubbing.
FinTech BNPL UPI AutoMandate ● Featured FinTech Project

Snapmint Pay & Credit: One-Click BNPL Checkout & Payment Gateway Cascade

FinTech Checkout & Risk Scoring Engine

πŸ’³ BNPL CUSTOMER JOURNEY User Story: Sub-30sec Credit Approval & Frictionless Checkout
πŸ›’
Customer Shopping
E-Commerce Cart
→
πŸ’³
Select EMI
Snapmint BNPL Option
→
⚑
Eligibility Check
Real-Time Score
→
πŸ†”
Instant KYC
PAN & Aadhaar Mandate
→
βœ…
Approval
Instant Sanction
→
πŸŽ‰
Checkout
+28% Conversion
→
πŸ“Š
Repayment Dash
AutoMandate Schedule
Executive Summary: Designed Snapmint’s zero-cost BNPL checkout flow and multi-acquirer gateway fallback cascade for first-time credit buyers. Increased checkout conversion rate by 28% and reduced payment drop-off by 42%.
+28%
Checkout Conversion Boost
42%
Drop-off Reduction
<30s
KYC & Credit Approval Speed
My Role & Competencies:
⚑ Product Strategy ⚑ User Research ⚑ PRD Specs ⚑ Wireframes ⚑ Prioritization ⚑ Stakeholder Management ⚑ Launch ⚑ Analytics
🧠 Product Thinking & Strategy Breakdown
01 Problem → 02 Insight → 03 Decision → 04 Impact
🎯
🎯 Problem Statement & User Pain
Target User First-Time Credit Buyers, E-Commerce Merchants & Risk Analytics Teams.
The Core Friction High checkout drop-off (65%+) on e-commerce carts due to complex credit application forms and payment gateway failures.
Frequency & Pain Point Frequency: High-intent daily online purchases ranging from β‚Ή2,000 to β‚Ή30,000.
Affected Business Metric E-Commerce Checkout Conversion Rate & First-Payment Default (FPD) Rate
πŸ‘€
πŸ‘€ User Research & Insights
Primary Personas Studied Ananya Roy (First-Job Professional) & Priyank Shah (D2C Brand Growth Lead).
User Pain Points Users abandon checkout when asked for 10+ bank details or when primary UPI payment gateway fails.
Key Behavioral Findings 82% of drop-offs happen at the credit approval step if processing takes longer than 45 seconds.
Journey Bottleneck Identified Single payment gateway bottleneck and slow manual KYC document verification.
βš–οΈ
βš–οΈ Product Strategy & Solution
Alternative Solutions Rejected Traditional credit card application flow requiring income proof documents.
Technical & Business Constraints Regulatory RBI guidelines for digital lending & AutoMandate e-NACH mandates.
Prioritization & MVP Cutoff Built multi-acquirer gateway fallback cascade for checkout before personalized EMI plan selector.
Risk Analysis & Guardrails Real-time risk scoring engine to auto-reject high-risk transactions without compromising sub-30sec checkout.
πŸš€
πŸ“ˆ Metrics & Business Impact
Chosen Product Solution Snapmint One-Click BNPL Checkout with sub-30sec alternate credit scoring and multi-gateway Auto-Cascade fallback.
Why It Worked Seamless 3-step checkout with instant credit sanctioning and auto-routing around failed payment gateways.
Quantified Business Metrics +28% checkout conversion rate boost; 42% payment drop-off reduction; <30sec average approval time.
Future Product Roadmap AI-driven personalized credit limit expansion and merchant co-branded zero-cost EMI campaigns.
TravelTech AI Homestay Copilot Dynamic Pricing πŸ’‘ INDEPENDENT PM CASE STUDY

MakeMyTrip Partner Connect: HostAssist AI & Dynamic Pricing Copilot

AI-Powered Homestay Host Automation & Revenue Optimization Engine

🏨 HOMESTAY HOST AUTOMATION JOURNEY User Story: Sub-5 Min AI Response & +21.4% RevPAR Lift
🏨
Guest Inquiry
Instant Booking Request
→
πŸ’¬
AI Auto-Reply
Multilingual Messaging
→
πŸ“Š
Dynamic Pricing
Rate Optimization Engine
→
πŸ“…
Calendar Sync
Multi-OTAs Inventory
→
🧹
Turnover Assist
Housekeeping Dispatch
→
⭐
Review Boost
3.2m Response & +21.4% RevPAR
Executive Summary: Conceptualized HostAssist AI for MakeMyTrip homestay hostsβ€”automating 24/7 guest inquiry responses, dynamic seasonal pricing rules, multi-OTA calendar synchronization, and review sentiment synthesis. Reduced guest response time by 98% (4.2h → 3.2 min) and boosted host RevPAR revenue by +21.4%.
3.2 Min
Guest Response Time (was 4.2h)
+21.4%
Host RevPAR Revenue Lift
94.8%
Guest AI CSAT Rating
My Role & Competencies:
⚑ Product Strategy ⚑ User Research ⚑ PRD Specs ⚑ Wireframes ⚑ Prioritization ⚑ Revenue Modeling ⚑ AI Copilots ⚑ Analytics
🧠 Product Thinking & Strategy Breakdown
01 Problem → 02 Insight → 03 Decision → 04 Impact
🎯
🎯 Problem Statement & User Pain
Target User Independent Homestay Hosts & Boutique Property Managers on MakeMyTrip & Goibibo.
The Core Friction Slow guest response times (4.2h average) and static pricing leading to 45%+ unbooked room nights.
Frequency & Pain Point Frequency: Multiple daily guest booking inquiries & check-in coordination messages.
Affected Business Metric Host RevPAR (Revenue Per Available Room) & Guest Booking Conversion
πŸ‘€
πŸ‘€ User Research & Insights
Primary Personas Studied Vikram Sharma (Villa Host, Goa) & Priya Nair (Coorg Cottage Operator).
User Pain Points 78% of hosts cited messaging fatigue and fear of complex manual dynamic pricing setup.
Key Behavioral Findings Guests who receive a response within 5 minutes are 3.4x more likely to confirm a booking.
Journey Bottleneck Identified Manual multi-OTA calendar updates causing double-booking cancellations.
βš–οΈ
βš–οΈ Product Strategy & Solution
Alternative Solutions Rejected Rule-based static auto-responders (robotic & incapable of custom guest Q&A).
Technical & Business Constraints Real-time calendar lock APIs and strict host review moderation compliance.
Prioritization & MVP Cutoff Prioritized AI Guest Auto-Responder + One-Click Dynamic Pricing Engine for MVP v1.0.
Risk Analysis & Guardrails Host override controls for automated price discounts to prevent revenue loss.
πŸš€
πŸ“ˆ Metrics & Business Impact
Chosen Product Solution HostAssist AI Copilot with automated guest messaging, dynamic pricing engine, and review synthesis.
Why It Worked Eliminated response friction and optimized room rates dynamically based on local demand surges.
Quantified Business Metrics 98% faster response (4.2h → 3.2 min), +21.4% RevPAR revenue lift, 94.8% CSAT rating.
Future Product Roadmap AI smart lock integration & automated guest identity verification (KYC).
FinTech Trading MTF Leverage Risk Engine πŸ’‘ INDEPENDENT PM CASE STUDY

Upstox MTF Smart Nudge: Margin Trading Facility & Risk Intercept Engine

Retail Trading Leverage & Automated Liquidation Prevention Platform

πŸ“ˆ TRADING LEVERAGE & RISK INTERCEPT JOURNEY User Story: 64% Square-Off Reduction & <10s UPI Top-Up
πŸ“ˆ
Stock Selection
High-Conviction Trade
→
⚑
MTF Nudge
Up to 4x Leverage Prompt
→
πŸ›‘οΈ
Risk Check
Dynamic Margin Buffer
→
πŸ“²
Smart Alert
Proactive Push Nudge
→
πŸ’³
Instant Add
One-Tap UPI Top-Up
→
πŸŽ‰
Position Saved
64% Square-Off Reduction
Executive Summary: Conceptualized an intelligent Margin Trading Facility (MTF) smart nudge and automated margin call risk engine for Upstox retail traders. Reduced unexpected position liquidations by 64%, increased MTF trade adoption by +38%, and enabled a sub-10 second one-tap UPI margin top-up flow.
64%
Reduction in Forced Square-Offs
+38%
MTF Trade Order Volume
<10s
One-Tap UPI Margin Top-Up
My Role & Competencies:
⚑ Product Strategy ⚑ User Research ⚑ PRD Specs ⚑ Wireframes ⚑ Risk Engineering ⚑ FinTech UX ⚑ Behavior Design ⚑ Analytics
🧠 Product Thinking & Strategy Breakdown
01 Problem → 02 Insight → 03 Decision → 04 Impact
🎯
🎯 Problem Statement & User Pain
Target User Active Retail Traders, Swing Investors & High-Frequency Equity Traders on Upstox.
The Core Friction Sudden forced position square-offs due to unexpected margin calls and confusing MTF leverage rules.
Frequency & Pain Point Frequency: High market volatility days when collateral values drop below maintenance margin.
Affected Business Metric Trader Churn, Forced Square-Off Rate & MTF Order Value
πŸ‘€
πŸ‘€ User Research & Insights
Primary Personas Studied Amit Verma (Swing Equity Trader) & Sneha Kapoor (FnO & Delivery Investor).
User Pain Points 72% of retail traders experienced panic liquidations due to delayed SMS margin call alerts.
Key Behavioral Findings Traders are 4.2x more likely to top up margin if presented with a 1-tap UPI drawer right inside the app.
Journey Bottleneck Identified Multi-step bank transfer flow required to add funds during market hours.
βš–οΈ
βš–οΈ Product Strategy & Solution
Alternative Solutions Rejected Generic SMS margin warnings without direct 1-tap in-app payment execution.
Technical & Business Constraints SEBI & exchange margin pledge compliance rules and real-time RMS risk engine sync.
Prioritization & MVP Cutoff Prioritized Smart MTF Order Nudge + 1-Tap UPI Margin Top-Up Drawer for MVP v1.0.
Risk Analysis & Guardrails Prominent risk disclosure modal detailing MTF interest rates before leverage activation.
πŸš€
πŸ“ˆ Metrics & Business Impact
Chosen Product Solution Upstox MTF Smart Nudge with contextual leverage prompts, real-time risk health meter, and 1-tap UPI margin top-up.
Why It Worked Transformed opaque risk alerts into proactive, actionable 1-click margin preservation steps.
Quantified Business Metrics 64% reduction in forced position liquidations, +38% MTF trade volume growth, <10s margin top-up speed.
Future Product Roadmap Automated portfolio stock-pledging for instant collateral margin release.
VERIFIED PROFESSIONAL CREDENTIALS

Professional Certifications

Industry-recognized certifications in Agile Project Management, Enterprise CRM Operations, and Agentic AI Architecture.

IBM
IBM • Coursera • SkillUp

IBM AI Product Manager Professional Certificate

Completed 10 intensive courses in Generative AI, prompt engineering (Chain of Thought, DALL-E, ChatGPT), AI product strategy, foundation models, and building AI-powered products.

AI Product Strategy Generative AI Prompt Engineering Foundation Models
G
Google • Coursera

Google Project Management Professional Certificate

Completed 7 intensive courses covering Agile & Scrum methodologies, sprint execution, project initiation, risk management, and AI-accelerated job search strategies.

Agile & Scrum Sprint Planning Risk & Execution AI Workflows
☁️
Salesforce • Pathstream

Salesforce Sales Operations Professional Certificate

Specialized in CRM architecture, lead pipeline management, sales opportunity tracking, and building executive dashboards across Salesforce Sales Cloud & Service Cloud.

Salesforce CRM Lead Pipeline Service Cloud Analytics Dashboards
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ServiceNow Executive

Micro-Certification – Agentic AI Executive

Certified in enterprise Agentic AI architecture, autonomous multi-agent workflow orchestration, LLM guardrails, and executive AI strategy implementation.

Agentic AI Workflow Orchestration LLM Guardrails Executive AI Strategy
PRODUCT MANAGEMENT PRINCIPLES & LESSONS

Beyond the Portfolio

What Building These Products Has Taught Me — Core leadership values shaping my product decisions.

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Start with the User

Understand the real workflow, friction points, and human context deeply before designing or coding any technical solution.

User-Centric Thinking
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Measure Outcomes

Every feature launched must tie back to a clear North Star metric, driving quantifiable customer satisfaction or business ROI.

Data-Driven Accountability
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Build Through Collaboration

Great products are forged through tight alignment between engineering, product design, business stakeholders, and end customers.

Cross-Functional Leadership
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Ship Small, Learn Fast

Launch tight MVPs early to gather empirical usage data quickly, iterating rapidly based on real-world feedback loops.

Agile Velocity & Iteration
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AI Should Amplify Humans

Deploy Artificial Intelligence to eliminate tedious manual friction, augmenting human judgment rather than adding complexity.

AI & Process Automation
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Business Value First

Every roadmap prioritization decision must align with scalable business growth, unit economics, and enterprise strategic goals.

Strategic Impact
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“My goal is not just to build products. My goal is to build products that customers love, teams are proud of, and businesses can scale.”
Souvik Ghosh • Product Philosophy

Let's Build Impactful Products Together

Open for Product Manager roles, APM positions, and product strategy discussions.

πŸ“„ Download Official CV (PDF) πŸ“₯ πŸ’Ό LinkedIn Profile β†’ βœ‰οΈ souvikd772@gmail.com πŸ“ž +91-8145354044