Rohit Kakkar | Profound

Rohit's Profound AI Rep

Rohit's stories span sell-side deal research, financial modeling, and consumer market analysis across tech and fintech.

Rohit Kakkar

Edges

Building Market Narratives from Ambiguous Data

Rohit takes markets that look unclear or negative on the surface and builds a credible forward-looking case from the available evidence. He does not wait for the data to be clean; he finds the signal that changes the read. This showed up in the senior care brief, where he came in skeptical and left with a conviction built on Japan market data and Indian real estate trends. It showed up again in TMS, where he mapped the structural economics of US freight from first principles to justify the market size. His process is consistent: gather secondary data broadly, find the credible sources with a forward-looking view, and build the narrative around what the data actually supports rather than what the brief assumed. The output is deal material that holds up under scrutiny from MDs with decades of industry experience.

Spotted in 2 Stories

Consumer Product Positioning Analysis

Rohit tracks how consumer brands build category positions, not just what they sell. He follows the strategic logic behind product launches, pricing decisions, and wave creation. He mapped how Minimalist built its position on clean labels and pricing discipline, drawing on the Ordinary's playbook. He analyzed SuperU's yeast protein launch and understood why its positioning worked: superior absorption versus plant protein, superior pricing versus whey. His process involves listening to founder podcasts, tracking D2C launches, and forming independent theses on why a product will or will not resonate with its target customer. This is self-directed research, not professionally assigned, which makes it a genuine signal of sector curiosity.

Spotted in 1 Story

Financial Modeling and Variance Analysis

Rohit builds and maintains financial models and traces variance back to its real drivers before presenting to leadership. He does not fit numbers to a narrative; he finds the actual cause. At Linde, he managed unit models across more than thirty plants, running monthly, quarterly, and annual cycles. The corporate account had no predictable trend, and he had to source the explanation from underlying reports each period. At TresVista, the modeling foundation from Linde gave him a speed and accuracy advantage over peers who had not done FP&A work before joining banking. This combination of model maintenance discipline and variance explanation is the analytical core he brings to research and deal work.

Spotted in 2 Stories

AI-Augmented Research Workflows

Rohit built a personal system for using AI tools to raise the quality of research and deal materials to senior professional standards. He does not use AI to generate output; he uses it to stress-test drafts and find weaknesses before they reach a reviewer. His workflow: draft, ask the AI to identify every reason the document could be rejected, iterate on the weaknesses surfaced, repeat. He ran ten or more versions on some documents before submitting. This approach helped him close the knowledge gap between a junior analyst and MDs with fifteen to twenty years of industry experience, producing materials that moved deals forward. As AI tools became standard at TresVista, output volume across the team increased by a multiple, and Rohit's early adoption of a structured AI workflow positioned him ahead of that shift.

Spotted in 2 Stories

Rohit Kakkar

Career Stories

Senior Care Fundraise: Building the Market Case from Scratch

At TresVista as Associate - Investment Banking

2024 - 2025

Building an AI-Augmented Deal Material Workflow at TresVista

At TresVista as Associate - Investment Banking

2024 - 2025

TMS Deck: Mapping a Market Nobody Explained Well

At TresVista as Associate - Investment Banking and Private Equity

2022 - 2024

Linde FP&A: Explaining Variance to Leadership Across 30-Plus Plants

At Linde as Executive - FP&A

2022 - 2022

Rural FMCG Survey: Primary Research in College

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