Bengaluru · Open to APM · Jr. PM · Business Analyst

Idon'tjustanalyzedata.Ibuildwhat'snext.

I've spent 2 years as a business analyst at Wipro and DXC — but I never stopped at just reviewing and running reports. I spotted problems worth solving, shipped two AI-powered tools from scratch, and sat in sprint planning alongside PMs. Now I'm making the switch official.

Read my storyHire me
~0
Years of experience
0%
Bottleneck identified
0%
Engagement increase
0%
Processing time cut
My Story

A business analyst
becoming a product manager.

I started out as a business analyst. My job was to look at tickets, track metrics, and keep things running. But the more I worked with the data, the more I kept noticing patterns that nobody was acting on.

I'd see the same types of tickets come in week after week. I'd watch engineers waste time on problems that could be solved with better tooling. And I kept thinking — why isn't someone building a fix for this?

“Good products come from understanding both the data and the people behind it.”

So I started doing it myself. I spotted a 28% operational bottleneck at Wipro and turned it into a change request. I shipped two AI-powered tools from scratch — an RCA agent and a workload balancer — both born from problems I saw first-hand. At Varcons, I'd already shipped a full app and grown engagement by 18%.

Two years of living inside user pain daily. I'm ready to own the product side end-to-end.

20
2020 – 2024

BE Computer Science

Jyothy Institute of Technology, Bangalore · GPA 8.22

Learned the fundamentals — REST APIs, databases, and how to break down problems systematically.

23
Jan – Mar 2023

Product & Engineering Intern

Varcons Technologies, Bengaluru

Built and shipped a social app from scratch. Made real product calls about what to build and what to skip. 18% engagement uplift.

24
Sep 2024 – Jun 2025

Business Analyst

DXC Technology · India

Mapped workflows end to end, cut case handling time by 24%, reduced incidents from ~12 to ~3 per release, and collaborated with PMs on user stories and backlog items.

NOW
Jun 2025 – Present

Business Analyst

Wipro Limited · Bangalore

Defined 4 KPIs, shipped two AI-powered tools (RCA Agent, Workload Balancer), eliminated ~50 analyst-hours/month, and embedded with PMs across sprint planning and roadmap reviews.

What I Bring

Six skills that
make a good PM.

Each one backed by something I've actually done — not just something I've read about.

Turning Data into Decisions

I don't just pull reports. I dig into why the numbers look the way they do and figure out what we should do about it.

Found a 28% bottleneck at Wipro that became a feature change request, saving ~6 hrs/month

Roadmap & Prioritisation

I've sat in sprint planning and roadmap reviews, helped evaluate trade-offs, and contributed to deciding what ships next.

Embedded with PMs at Wipro — contributed to PRD drafts and evaluated release trade-offs

Working Across Teams

I talk to engineers, PMs, designers, and business stakeholders regularly. I gather requirements, understand constraints, and keep people aligned.

Collaborated with PMs at DXC to turn operational findings into user stories and backlog items

Understanding Users

I've built UIs and watched how real people use them. I've mapped user journeys for both end users and internal engineers. I think about who's on the other side.

18% engagement uplift from user-behaviour-driven feature decisions at Varcons

Technical Understanding

CS degree. I've written production code in React, TypeScript, and Appwrite. Azure certified. I can have real conversations with engineers about what's feasible.

AZ-900 certified · Built and shipped a full-stack app as the sole developer

Writing Clear Specs

I've written user stories, requirement docs, and detailed workflow specs. At Wipro I authored feature change requests and owned product specs through launch.

Owned end-to-end spec for the RCA AI Agent — user journeys, edge cases, acceptance criteria
Experience

What I've done,
and what it means.

I've been a business analyst on paper — but the work I've done looks a lot more like product management.

Wipro Limited

Business Analyst

Jun 2025 – PresentCurrent Role
28%
Bottleneck surfaced
6 hrs
Manual effort saved / month
~50 hrs
Analyst-hours freed / month
4
KPIs defined
  • →Defined 4 engineering performance KPIs from scratch, surfaced a 28% bottleneck in support operations, and authored the change request that cut manual effort by ~6 hrs/month.
  • →Automated recurring ad-hoc data requests into self-serve Power BI dashboards — eliminating ~50 analyst-hours monthly and freeing the team for product-critical work.
KPI DefinitionPower BISprint PlanningPRD WritingUser StoriesAgile
DXC Technology

Business Analyst

Sep 2024 – Jun 2025
24%
Case handling time cut
12→3
Incidents per release cycle
3
Critical datasets validated
  • →Mapped support workflow end to end, identified where cases were stalling, and proposed process changes that cut average case handling time by 24%.
  • →Built data validation logic across 3 critical datasets, catching error classes pre-production and reducing downstream incidents from ~12 to ~3 per release cycle.
Workflow AnalysisUser StoriesBacklog ContributionData ValidationPM Collaboration
Varcons Technologies

Product & Engineering Intern

Jan – Mar 2023First Ship
18%
Engagement increase
1
Product shipped solo
  • →Owned end-to-end delivery of a consumer social app — from feature scoping and UX flows to shipping production code in React, TypeScript, and Appwrite, driving an 18% engagement uplift.
  • →Made product prioritisation calls (infinite scroll vs performance optimisation) by evaluating user behaviour patterns and balancing technical constraints with business goals.
ReactTypeScriptFeature DecisionsUX DesignFull Ownership
Projects

Things I've
designed & built.

All three came directly from problems I saw in my analyst role at Wipro. I didn't wait for someone to assign them — I identified the gaps and made the case to build.

0 to 1 Product Build

RCA AI Support Agent

An AI first-responder that troubleshoots, resolves, and escalates — so engineers don't have to.

Problem

Recurring first-contact resolution failures were affecting ~30% of incoming tickets. Engineers were spending time on repetitive issues with known solutions — and manually writing up the same tickets every time.

Solution

Identified the pattern in support data, defined the product vision for an AI-powered RCA assistant with guided troubleshooting and context-aware video resolution, and owned the end-to-end spec through launch.

PM Angle

I mapped the full user journey for both sides — the customer hitting an issue and the engineer handling it. The escalation flow and auto-documentation logic were designed with both perspectives in mind.

Key Features

  • →Guided troubleshooting with context-aware video-based resolution
  • →Smart escalation workflows routing unresolved cases to the right engineer tier
  • →Auto-documentation logic — zero manual ticket write-ups for engineers
  • →Duplicate effort cut on ~35% of escalations

Reduced average engineer handling time by ~15 min/ticket. Cut duplicate documentation effort on ~35% of escalations.

~30%
Tickets affected at baseline
15 min
Saved per ticket
35%
Escalations de-duplicated
AI Product0 to 1User Journey MappingEscalation DesignProduct Spec
Product Design & Strategy

Support Engineer Performance Dashboard

Giving managers a clear, data-backed picture of how 200+ engineers are actually performing.

Problem

I noticed managers had no single place to see engineer performance. Ticket resolution times, acceptance ratios, and monthly trends were scattered across different systems — so coaching decisions were based on gut feel.

Solution

I identified the gap in manager visibility, scoped the requirements, and designed a dashboard tracking ticket acceptance ratio, mean time to resolution, and review metrics for 200+ support engineers.

PM Angle

I treated managers as the primary user. The information hierarchy was designed around their weekly coaching routine — what they need to see first, what actions they can take, and what they can export for reviews.

Key Features

  • →AI-driven insights to separate customer-side vs engineer-side issue impact
  • →Monthly rankings and coaching recommendations generated automatically
  • →Live tracking of acceptance ratio, MTTR, and volume trends
  • →Manager-facing review layer with exportable summaries

Managers could coach with data instead of guesswork. Monthly rankings and recommendations directly influenced team allocation and training decisions.

200+
Engineers tracked
3
Core KPIs
AI
Insights layer
Dashboard DesignKPI TrackingAI IntegrationStakeholder ToolProduct Strategy
AI Product Design

AI Workload Balancer & Capacity Planner

Replacing gut-feel ticket assignments with data-driven routing — so the right engineer gets the right ticket, every time.

Problem

Ticket distribution was completely manual and uneven. High-complexity cases kept landing on the same senior engineers repeatedly, SLA breaches were piling up, and nobody had visibility into who was actually available or quietly burning out.

Solution

Defined a 'balance ratio' metric, designed an XGBoost-based complexity scoring engine predicting handling time via issue type, historical patterns, and sentiment — improving assignment accuracy by ~2x vs. manual baseline. Built a manager-facing capacity view that auto-recommends optimal assignments in real time.

PM Angle

I started with the metric — 'balance ratio' — and worked backwards from it. Once I had a way to measure fairness, I could define what good looked like and design the system around that target. I scoped two distinct user journeys: the manager needing live workload visibility, and the engineer needing clarity on their queue.

Key Features

  • →XGBoost complexity scoring engine predicting handling time from issue type, history, and sentiment
  • →Real-time capacity tracking with predictive load forecasting for optimal routing
  • →Auto-recommended assignments — ~2x accuracy improvement vs. manual baseline
  • →AI-generated alerts surfacing at-risk engineers 48 hrs before burnout escalates

Replaced gut-feel assignments with data-driven routing across 3 teams — SLA breach frequency dropped ~30% and burnout risk surfaced 48 hrs earlier.

~2x
Assignment accuracy
~30%
SLA breach reduction
48 hrs
Earlier burnout alerts
AI ProductXGBoostCapacity PlanningSLA ManagementProduct Metrics
Live Builds

Shipped, deployed,
and clickable.

The case studies above are work I can't link. These are builds I scoped, shipped, and deployed myself — open them, click around, read the specs.

AI Product Prototype

Atlas

An analyst triage tool for AI-detected objects in overhead imagery — built for the moment the model is good enough and the human becomes the bottleneck.

The full PM loop, solo: PRD → build → deploy → recorded walkthrough. Scoped and shipped in 5 days.
Next.jsYOLOv8SupabaseVercel
Live demoPRDWalkthroughCode
Read the case study
ETL + Analytics

FreightLens

A freight analytics pipeline turning 8,000 messy simulated FTL shipment records into carrier scorecards and lane economics — cleaning, warehouse, and dashboard included.

End-to-end data product thinking: raw → cleaned → SQLite warehouse → KPI dashboard, with the SQL analysis layer documented in the repo.
PythonpandasSQLiteSQLChart.js
Live dashboardCode
Read the case study
Enterprise SaaS

ODR Platform

A multi-tenant online dispute resolution platform — formal case-lifecycle state machine, AI case triage, secure multi-party messaging, and an API layer for platforms to file disputes programmatically.

Comfort with enterprise-grade complexity: multi-tenancy, row-level security, HMAC-signed webhooks, and an AI intelligence layer — designed and shipped alone.
Next.jsTypeScriptSupabaseClaude API
Live platformCode
Read the case study
How I Think

My approach
to product work.

This Portfolio is a Product

Seriously — I treated it like one

  • User: A hiring manager or PM lead, probably short on time, scanning through dozens of profiles looking for someone who actually gets it.
  • Problem: Most analyst portfolios just list tasks. They say what was done, but not what was built or why it mattered.
  • Solution: A portfolio built around outcomes, decisions, and real product work — not just a list of responsibilities.

Goal: get callbacks from PM-hiring companies Success signal: recruiter spends >90s on the site Iteration: collect feedback, improve copy and structure

How I Work Through a Problem

The process I come back to every time

  • Start with the problem: What's the business goal? Who are we building for? What does good look like in 6 months?
  • Know the user: Who specifically? What's their pain point? What job are they trying to get done?
  • Prioritise honestly: RICE, MoSCoW, effort-impact — use whatever fits, but be ready to explain why.
  • Measure what matters: Every feature should have a way to tell if it worked. If you can't measure it, you're guessing.

At Wipro: saw recurring support failures in the data, pitched the RCA Agent to leadership, owned the spec, shipped it. That's the loop.

Why Me

Three things worth
knowing about me.

01
01

I've done the work without the title

I didn't wait for someone to call me a PM. As a business analyst, I shipped two AI-powered tools, wrote specs, sat in sprint planning, and pitched ideas to leadership. The work came before the title.

02
02

I know what support teams actually need

I've lived it. I've seen the tickets, tracked the metrics, and felt the pain points first-hand. That gives me a perspective on building internal tools that most PMs have to guess at.

03
03

I can talk to engineers — for real

CS degree. I've shipped React and TypeScript code in production. Azure certified. I don't need a translator between business and technical conversations.

Targeting APM & Product Analyst roles · B2B SaaS · Bengaluru & Remote
Get in Touch

Interested in
working together?

I'm looking for teams that care about building things well — where clear thinking and real experience both matter. Happy to chat.

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