Parth's Profound AI Rep
Parth turns ambiguous briefs and raw market data into structured, decision-ready outputs.
Parth Garg
Edges
Building Research Automation Systems
Parth builds systems that let teams move faster without losing rigor. His instinct is to identify where recurring manual work is slowing things down and replace it with a reusable, automated solution. At Verity, he built three distinct tools: an automated weekly league table refresh for EMEA and global markets, a Microsoft Copilot prompt that reconstructs audited financial statements from annual reports directly into Excel, and a VBA-powered multi-filter tool that lets clients apply complex criteria to large data dumps without manual intervention. The pattern across all three is the same: he sees the friction, understands the underlying need, and builds something that removes the problem permanently rather than solving it once. For a team that runs recurring research deliverables, this kind of infrastructure thinking compounds over time.
Spotted in 2 Stories
Synthesizing Macro Signals Into Market Narratives
Parth connects macroeconomic signals to market behavior and translates that connection into clear written narratives. He does not stop at the data; he explains the mechanism. In his monthly DCM reports at Verity, he linked Trump tariff uncertainty to DCM slowdown and traced Fed rate decisions to their direct impact on bond pricing, writing commentary that gave clients a causal explanation for what the data showed. On an Indian equity market outlook, he proactively added GDP and inflation analysis that was not in the brief, explaining how repo rate changes affect purchasing power and how GDP expectations drive investor sentiment. The addition was accepted into the final deliverable. For a research role that requires forming and defending a market view, this is the pattern that matters.
Spotted in 2 Stories
Structuring Ambiguous Research Briefs
Parth does not guess when a brief is unclear. He maps the possible interpretations, confirms the right path with the client, and then commits fully to the chosen approach. On a US M&A confidential information memorandum, the instructions for share price performance and valuation multiples were both unclear. He listed the options for each, including which comparators to use and how to handle a company with limited broker coverage, and got confirmation before proceeding. On the FTSE 250 investor screening exercise, he recognized after the first iteration that the client's actual need was different from the standard approach, and rebuilt the model to match what they were really asking for. For a research role where briefs are often incomplete, this approach prevents wasted effort and keeps the output aligned with what the client actually needs.
Spotted in 2 Stories