Portfolio · 2026

Thirumaran V N

Associate Product Manager | Automotive & SDV | Research-Led · Data-Driven · Systems-Oriented

"I've owned four end-to-end product intelligence systems at a deep-tech Automotive & SDV startup — from problem definition through automation and delivery. Now bringing that into Product Management."
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Thirumaran V N
01About

A product mind, built across the whole stack.

I'm Thirumaran — a product and research professional who grew from a research intern to owning end-to-end product intelligence systems at Creamcollar, a deep-tech startup operating at the intersection of Automotive, SDV, and EdTech.

Over the years, I've worked across almost every function a product touches — research, data, operations, finance, platform development, and product strategy. That breadth isn't accidental. It gave me a ground-level understanding of how organizations actually work, where problems really come from, and what it takes to move something from a vague idea to something that ships.

I think in systems. I ask why before how. I follow the problem, not the solution.

Now I'm bringing that into Product Management — four shipped systems, 10+ structured case studies, and a physics-trained mind that asks why before how.

“A PM's job is wide by design — I've intentionally worked across enough of it to know that the hardest part isn't building the solution. It's making sure you're solving the right problem, for the right people, at the right time.”
02Core Skills

The toolkit behind every decision.

Product Management

  • Product Strategy
  • PRD Writing
  • Roadmapping
  • Feature Prioritization
  • Agile / Scrum

Research & Discovery

  • User Research
  • JTBD
  • First Principles
  • Market Sizing (TAM/SAM/SOM)
  • Competitive Analysis

Data & Systems

  • Pipelines & Automation
  • Dashboard Design
  • Data Monitoring
  • Validation Frameworks

Product Intelligence

  • Competitive Analysis
  • Benchmarking
  • Report Generation
  • Trending Signal Detection

Domain Knowledge

  • Automotive & SDV
  • EdTech
  • Mobility
  • Fitness Tech

Tools

  • Python
  • SQL
  • Power BI
  • Neo4j
  • Figma
  • Lovable
  • PostgreSQL
  • Notion
  • Jira

Design & Prototyping

  • UX Research
  • Heuristic Evaluation
  • Vibe Coding
  • Journey Mapping
03Experience

Where I've shipped work.

Present

Creamcollar — Junior Research Analyst

Current Role · Promoted from Data Intern

This is where I stopped executing other people's frameworks and started building my own. Owned four major initiatives end-to-end — from requirement definition to automation to delivery.

  • Automotive Product Intelligence

    Designed and shipped an end-to-end automated competitive intelligence system from scratch.

  • Trending Company Detection

    Built the signal engine that surfaces fast-rising SDV/automotive companies — feeds 3+ downstream projects.

  • Domain Ontology

    Owned the relationship model and Neo4j knowledge graph for the automotive ecosystem.

  • Name Variant Pipeline

    Defined and shipped the normalization pipeline that fixes deduplication across the full research database.

What this taught me

Identifying what the business doesn't know yet, building the system to know it, and making sure that knowledge stays accurate, accessible, and useful.

See the projects I owned
Earlier

Creamcollar — Data Intern

Promoted from Research Intern

Moved into the data team with a clear mandate: build reliability into how we collect and validate information.

  • Data Collection

    Structured sourcing pipelines for automotive and SDV datasets.

  • Validation Framework

    Designed and executed the framework for data quality assurance.

  • Execution

    Ran validation checks end-to-end across live datasets.

What this taught me

Bad data makes bad decisions. I learned to think about data not just as input, but as a product that needs its own quality bar, ownership, and maintenance logic.

Start

Creamcollar — Research Intern (Part-Time, During M.Sc)

Startup · Automotive, SDV & EdTech

Started here while finishing my M.Sc in Physics. Not just observing — contributing.

  • Automotive & SDV Ecosystem

    Secondary research feeding into business and product decisions.

  • Data Product

    Data validation and research supporting product development.

  • EdTech Platform

    Research inputs shaping syllabus and platform development.

  • Operations

    Managed office operations, events, and workshops end-to-end.

  • Finance

    Managed expense tracking and financial coordination.

What this taught me

Early-stage startups don't have walls between functions. I learned to context-switch fast, take ownership without being asked, and see how every part of an organization connects to the product.

04Selected Projects

Case studies built like product artifacts.

Each project framed as Problem → What I Built → Impact — the way a PM would describe their work.

01Live System
Solo Owner
Product Intelligence · Automation · B2B Internal Tool

Automotive Product Intelligence — End-to-End Automated Competitive Intelligence System

No structured system existed to track, validate, and monitor automotive product data across the SDV ecosystem at scale.

Architecture
Data Sources→
Extraction Pipeline→
Validation Layer→
Monitoring Dashboard→
Competitive Reports
100% AutomatedSole OwnerLive Dashboard
What I Built
  • ·End-to-end data extraction pipeline for automotive products across the SDV ecosystem
  • ·Automated data validation framework with quality checks and error flagging
  • ·Real-time monitoring dashboard for continuous data tracking and updates
Impact
  • ·Eliminated manual research effort through full pipeline automation
  • ·Delivered consistent, validated competitive intelligence to inform decisions
  • ·Benchmarking directly supported strategic product positioning

Note: This is proprietary internal work. I can walk through the architecture, decisions, and outcomes in detail — but cannot share screenshots or data.

02Live System
Solo Owner
Market Intelligence · Pipeline · Strategic Tool

Trending Company Identification — SDV & Automotive Ecosystem Signal Detection

No systematic method to surface fast-rising companies in the automotive/SDV space before they became mainstream knowledge.

Architecture
Parameter Definition→
Data Collection→
Scoring Engine→
Ranking Pipeline→
Downstream Projects (3+)
3+ Downstream ProjectsSignal Engine
What I Built
  • ·Defined parameters and scoring logic to identify trending companies
  • ·Built complete end-to-end identification and ranking pipeline
  • ·Output feeds Product Intelligence, Ontology, and Client Research projects
Impact
  • ·Acts as an intelligence backbone — informs 3+ downstream projects
  • ·Reduces research lag and improves speed-to-insight for the entire team

Note: This is proprietary internal work. I can walk through the architecture, decisions, and outcomes in detail — but cannot share screenshots or data.

03Live System
Solo Owner
Knowledge Graph · Data Architecture

Automotive Domain Ontology — Relationship Mapping & Knowledge Graph

No structured representation of relationships between companies, products, and technologies in the SDV ecosystem.

Architecture
Entity Definition→
Relationship Mapping→
Neo4j Knowledge Graph→
Query Layer→
Cross-Domain Analysis
Neo4jQueryable Graph
What I Built
  • ·Ontology framework design and relationship creation logic
  • ·Knowledge graph built using Neo4j
  • ·Data extraction, validation, and graph population pipeline
Impact
  • ·Created a structured, queryable knowledge layer enabling deeper cross-domain research and product analysis

Note: This is proprietary internal work. I can walk through the architecture, decisions, and outcomes in detail — but cannot share screenshots or data.

04Live System
Solo Owner
NLP Pipeline · Data Engineering

Company Name Variant Identification Pipeline

Inconsistent company name formats across datasets caused duplication and misattribution in research outputs.

Architecture
Raw Entity Names→
Variant Detection→
Normalization Engine→
Deduplicated Database
DeduplicationNormalization
What I Built
  • ·Automated pipeline to identify and normalize company name variants across categories
Impact
  • ·Improved data accuracy and deduplication across the full research database

Note: This is proprietary internal work. I can walk through the architecture, decisions, and outcomes in detail — but cannot share screenshots or data.

05Case Study
Concept Project
PM Case Study · Mobility · User Research

Fixing Uber's Pickup Experience in High-Friction Urban Environments

GPS-pin-only coordination fails in airports, malls, and IT parks — causing cancellations and frustration for both riders and drivers.

JTBDTAM/SAM/SOMPrototype
What I Built
  • ·JTBD framework across Riders, Drivers, and Platform
  • ·First Principles decomposition of coordination failure
  • ·Market sizing (TAM/SAM/SOM), user segmentation, regulatory scan
Impact
  • ·Research-to-product roadmap for reducing pickup failure and improving marketplace efficiency
View Full Case Study
06Case Study
Concept Project
Product Design · Prototype · Mobility

Smart Hail Go — Concept Product for Context-Aware Pickup Coordination

Ride-hailing pickup breaks down in complex environments because drivers and riders lack shared spatial context.

Clickable PrototypeDual User Flows
What I Built
  • ·Smart pickup point recommendation engine
  • ·Landmark-based selection + real-time coordination workflows
  • ·End-to-end prototype: booking → pickup guidance → tracking → payment
Impact
  • ·Clickable prototype demonstrating measurable reduction in coordination failure across complex pickup zones
View Full Case Study
07Case Study
Concept Project
PM Case Study · Consumer App · Retention

VitaFit — Reversing Churn Through Behavioral Design

30-day retention below benchmarks; users drop off after 2–3 weeks with no emotional connection to the platform.

20–30% Retention40% WAU ↑2× Sessions
What I Built
  • ·Root-cause analysis of retention failure
  • ·Feature design: XP, badges, streaks, leaderboards, redeemable rewards
  • ·Community challenges: group missions, instructor events, accountability
Impact
  • ·20–30% improvement in 30-day retention (projected)
  • ·40% increase in weekly active users within 90 days (projected)
  • ·2× session completion rate (projected)
View Full Case Study
08Case Study
Concept Project
PM Case Study · EdTech · AI Product

AI-Powered Personalized Learning Platform — End-to-End Product Blueprint

Generic course delivery fails to adapt to individual learner needs, reducing engagement and completion.

Full PRDMicroservices3 Personas
What I Built
  • ·Full PRD covering Learners, Instructors, and Admin personas
  • ·AI course recommendation + chatbot + gamification + certification + mentoring
  • ·Microservices architecture, API design, analytics layer, platform integrations
Impact
  • ·Scalable, production-ready AI learning blueprint focused on retention and personalized outcomes
Case Study Coming Soon
09Case Study
Concept Project
UX Research · Product Thinking

Railway Booking UX — Reducing Cognitive Load at the Point of Decision

Visual clutter, cryptic abbreviations, and poor system feedback cause drop-offs in the booking funnel.

10 HeuristicsPrioritized Roadmap
What I Built
  • ·Nielsen's 10 Heuristics applied to the full booking flow
  • ·UX laws mapped: Tesler's, Hick's, Fitts's, Figure-Ground
  • ·Evidence-based redesign proposals with priority ranking
Impact
  • ·Usability roadmap to reduce cognitive load and improve booking conversion
View Full Case Study
10Case Study
Concept Project
Product Discovery · JTBD · Feature Strategy

Why Spotify's Collaborative Playlist Isn't Sticking — A JTBD Analysis

Low adoption of a high-potential social feature despite Spotify's large active user base.

JTBDBehavioral Mapping
What I Built
  • ·JTBD + First Principles applied to feature adoption failure
  • ·Behavioral barrier mapping: control, friction, passive listening preference
  • ·Competitive behavior analysis (single-DJ model, passive sharing)
Impact
  • ·Research-led feature strategy to increase collaborative engagement and social music experiences
View Full Case Study
05Contact

Let's build something worth using.

Open to Associate PM and PM roles at product-first startups and growth-stage companies. Especially interested in Automotive, SDV, EdTech, and B2B SaaS.

thirumaranvn@gmail.com+91 93446 45743linkedin.com/in/thirumaranvngithub.com/thiru-maran395