Shravan kumaar

About

Shravan kumaar works in AI GTM & Growth, AI automation & agents and AI engineering, based in San Francisco. GTM Engineer | AI & Workflow Automation | Bay Area | 4+ Years of Work Experience. Public projects on GitHub include Aerospace-supply-chain-risk-ai (End-to-end aerospace supply chain risk scoring pipeline with AI-generated procurement briefs), Signal To Pipeline (GTM signal-to-pipeline engine: buying signals (Apify, funding, leadership) → Clay enrichment + scoring → n8n…) and Bart Ridership Analysis (Portfolio data analysis project: BART ridership trends, pandemic recovery, station revenue rankings, and…), mostly written in Python and Jupyter.

Projects 6

• github.com

  Aerospace-supply-chain-risk-ai

  End-to-end aerospace supply chain risk scoring pipeline with AI-generated procurement briefs

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  Signal To Pipeline

  GTM signal-to-pipeline engine: buying signals (Apify, funding, leadership) → Clay enrichment + scoring → n8n → Salesforce, with capacity-aware AE/BDR routing and Claude-written outreach drafts (validated, never auto-sent). Reports + dashboard included.

  github.com
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  Bart Ridership Analysis

  Portfolio data analysis project: BART ridership trends, pandemic recovery, station revenue rankings, and 2030 forecasting using Python, pandas, seaborn, and Excel automation.

  github.com
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  Gpu Deal Desk

  A working quote-to-cash deal desk for a GPU cloud: HubSpot pipeline, versioned price book, approval matrix, and a quote engine that blocks rather than guesses. Synthetic data.

  github.com
• github.com

  B2B-SaaS-GTM-analytics

  End-to-end B2B SaaS GTM analytics pipeline: Salesforce CRM reporting, PostgreSQL analytics layer, and a 4-page Tableau BI dashboard covering pipeline health, sales productivity, forecasting, and retention.

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  B2B Sales Forecasting Ensemble

  Forecasted quarterly B2B steel sales for 75 customers using LightGBM, XGBoost, CatBoost ensemble with Optuna tuning

  github.com