Headline

GTM @ InCommon | Kelley School of Business

About

GTM @ InCommon Clarity over clever. Positioning over promotion. Resonance over reach.

Location

Mumbai

AI stack

claude code

langchain

Browser Use

Exa

Firecrawl

Zapier

Work experience

Growth Strategy and Revenue Operations at InCommon, Jun 2026 - Present · 3 mos, Pune District, Maharashtra, India, I lead GTM and Partnerships at InCommon

GTM Engineer at auntedna.ai, Jan 2026 - Jun 2026 · 6 mos, United States, Designed and deployed a multi-agent investor research pipeline using Claude Code, orchestrating 5 specialized subagents integrated with MCP servers (Prospeo, Gmail, Clay), cutting investor research time to under 5 minutes per prospect

Graduate Assistant at Indiana University - Kelley School of Business, Aug 2025 - Dec 2025 · 5 mos, Bloomington, Indiana, United States, Graduate Assistant for X-501 • Artificial Intelligence (Prof. Alan Dennis) • Design Thinking (Prof. Michael Peck) • Product Management (Prof. Nick Baker)

Student Data Scientist at General Motors, Aug 2025 - Dec 2025 · 5 mos, Remote, • Leveraged Time Series Foundation Model (Moment) to generate embeddings of NASA C-MAPSS turbofan engine data, enabling interpretable feature representations for Remaining Useful Life (RUL) prediction. • Designed and benchmarked a hybrid architecture combining TSFM embeddings with classical ML models (SVR, Random Forest, LightGBM, Neural Net), achieving competitive accuracy while reducing training time by >1000× compared to deep learning baselines. • Demonstrated strong few-shot learning performance, showing that lightweight models trained on as little as 10% of labeled data could still match or surpass traditional DL models, offering a scalable solution for predictive maintenance in data-scarce industrial environments.

Product Analyst at Meytier Inc., May 2025 - Aug 2025 · 4 mos, New York City Metropolitan Area, • Researched and mapped the full end-to-end hiring journey, leading 5 cross-functional workstreams that identified opportunities to integrate intelligence (AI APIs) into the platform. Insights directly informed the product roadmap and shaped how AI could reduce friction across recruiter and candidate workflows. • Developed a proof-of-concept leveraging Groq’s ultra-low-latency inference to accelerate AI responses from ~20 seconds to just 5 milliseconds. The PoC was adopted into production, dramatically improving platform responsiveness, enhancing user experience, and reducing drop-offs due to delays. • Conducted 6 in-depth user interviews with hiring managers and recruiters to surface unmet needs around recruiting metrics. Translated insights into 3 new hiring metrics tied to platform data and pain points, which were successfully deployed in a subsequent release to increase decision-making clarity for clients. • Redesigned data delivery with client-side caching, cutting server requests by 60% and improving response times by 45%. This optimization made the platform significantly more scalable while providing a smoother, faster, and more reliable user experience.

Education

Master of Science - MS, Information Systems, Management Information Systems, General, Indiana University - Kelley School of Business

Bachelor of Technology - BTech, Computer Engineering, Dwarkadas J. Sanghvi College of Engineering