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  • University Of Washington
  • United States
  • 06:27 (UTC -12:00)
  • LinkedIn in/uvabolla

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BUVKAUSHIK/README.md

Uva Bolla

Product-minded builder working across AI, data, cybersecurity, and decision systems.
Seattle, WA · MS Information Management, University of Washington

I build products where the hard part is not only the code — it is understanding the user, the workflow, the risk, and the decision that needs to get better.

My path has been non-linear: civil engineering in India, a construction labor marketplace, enterprise insurance platforms at Cognizant/John Hancock, and now applied AI/data products. That mix shaped how I work: start with the real problem, talk to users, map the system, measure what matters, and ship something that people can actually use.

Right now I am focused on AI search readiness, product analytics, decision intelligence, cybersecurity workflows, and practical AI systems for messy real-world domains.


How I Think About Building

  • Product first: What user pain is this solving, and why does it matter now?
  • Systems second: What data, workflow, constraints, and failure points sit underneath it?
  • Execution always: Can we prototype it, test it, measure it, and improve it quickly?
  • Responsible by default: Especially when the domain touches privacy, compliance, security, or public trust.

I like projects that sit at the intersection of product judgment and technical execution — dashboards that guide decisions, AI tools that explain their reasoning, workflows that reduce friction, and prototypes that can turn into real products.


Current Direction

I am especially interested in:

  • AI Search / AEO / GEO: helping teams understand how answer engines read, cite, and recommend content.
  • Product Analytics: building measurement loops that connect user behavior to business outcomes.
  • Applied ML: using models for forecasting, prioritization, risk detection, and operational decision-making.
  • Cybersecurity + Threat Intelligence: turning noisy security signals into structured, explainable intelligence.
  • Civic and Social Impact Tech: building accessible tools for public understanding and participation.

Selected Projects

Project What it does Why it matters
AEO Pre-Publish Scorer Scores whether a webpage is ready for AI/answer-engine discovery using page extraction, rule-based checks, and LLM judgment. Moves content teams from “publish and wait” to pre-launch decision-making.
Crest.ai A deeper AEO/GEO product direction for diagnosing how AI systems understand, cite, and compare business content. Explores the shift from traditional SEO to AI-mediated discovery and agent readiness.
HarvestIQ County-level corn and soybean yield forecasting using NOAA weather data, USDA yield data, PySpark, XGBoost quantile regression, Delta tables, and MLflow. Turns weather volatility into early-warning agricultural risk signals.
DoorDash Table Mode Product prototype for dine-in group ordering, QR-based table joining, receipt upload, split allocation, retries, and edge states. Shows how a consumer workflow can be mapped from user friction to product states.
FinOps Checkout Analytics Privacy-first checkout analytics using PostHog, Stripe webhooks, experiments, session replay, and Vercel deployment. Connects product instrumentation to conversion, payment truth, and experimentation.
Washington State PCO Guide Accessible civic education site for young Washington voters learning about Precinct Committee Officers. Makes local civic participation easier to understand for first-time and younger voters.
Churn Navigator Churn prediction and engagement system using MongoDB, Spark, Airflow, FastAPI, Docker, Kubernetes, and n8n automation. Demonstrates an end-to-end data-to-action retention workflow.
EcoPulse Carbon footprint tracking app for employees with goals, recommendations, charts, and progress tracking. Applies product design and data visibility to sustainability behavior change.
Threat Feed Aggregator Threat intelligence feed aggregator using public IOC sources and cybersecurity workflow thinking. Turns scattered threat data into a more usable analyst workflow.

Work I Bring Into Projects

Enterprise product delivery
At Cognizant, I worked on John Hancock insurance platforms across testing, automation, stakeholder coordination, release readiness, API validation, SQL checks, dashboards, and production-quality delivery. That experience made me comfortable with regulated workflows, messy systems, and the discipline needed to ship without breaking trust.

Product + founder mindset
I have worked on early product ideas from field research to prototype, including construction labor matching, civic engagement, sustainability tracking, and AI search readiness. I care about whether the product survives contact with real users — not just whether the demo looks good.

Data + AI execution
I work across Python, SQL, Power BI/Tableau, Snowflake concepts, Spark, FastAPI, Flask, React, Vite, Node/Express, PostHog, Stripe, MLflow, Docker, and GitHub workflows. I use tools as means to build clearer products, not as the headline by themselves.


Technical Toolkit

Product / Delivery: PRDs, user research, requirements mapping, acceptance criteria, release planning, stakeholder communication, UAT, go/no-go readiness, roadmap thinking
Data / Analytics: SQL, Python, pandas, Power BI, Tableau, Snowflake, PostHog, data modeling, funnel analysis, experimentation
AI / ML: XGBoost, scikit-learn, Spark, MLflow, LLM evaluation, prompt workflows, AI search/AEO analysis
Engineering: JavaScript/TypeScript, React, Vite, Next.js, Node/Express, Flask, FastAPI, Docker, Git/GitHub, Selenium/WebDriver, TestNG, REST APIs
Security: threat intelligence, public IOC feeds, MITRE ATT&CK thinking, logging/monitoring mindset, privacy-aware product design


What I Am Looking For

I am aiming for roles where I can sit close to both the customer problem and the technical system behind it:

  • Product Manager / Technical Product Manager
  • Forward Deployed Engineer / Solutions Architect
  • Program Manager for technical, data, AI, or platform teams
  • Business/Data Analyst roles with strong product and systems ownership

The through-line is simple: I like taking ambiguous problems, making them concrete, and building the first useful version.


Writing


Recent Activity ⚡

  1. 🎉 Merged PR #2 in BUVKAUSHIK/BUVKAUSHIK
  2. 💪 Opened PR #2 in BUVKAUSHIK/BUVKAUSHIK

LinkedIn · Portfolio · Substack · Email

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  1. Threat_Feed_Aggregate Threat_Feed_Aggregate Public

    A simple Flask-based web application that aggregates and displays real-time threat intelligence data from public sources like AbuseIPDB (malicious IPs) and URLHaus (malicious URLs). This project de…

    Python 1

  2. Capstone Capstone Public

    Washington State PCO Guide A modern, accessible website designed to educate young voters in Washington State about Precinct Committee Officers (PCOs) and local political engagement opportunities.

    TypeScript 1

  3. Churn_Navigator Churn_Navigator Public

    Monitor and predict user churn, then take proactive steps (e.g., sending personalized offers) to retain subscribers.

    Python

  4. doordash-table-mode doordash-table-mode Public

    An interactive React demo that simulates the end-to-end dine-in experience on DoorDash — from selecting a restaurant to splitting the bill among friends. Live Demo

    CSS

  5. e-commerce-app-design e-commerce-app-design Public

    Privacy-first, end-to-end checkout analytics powered by PostHog + Stripe + Vercel

    TypeScript

  6. HarvestIQ HarvestIQ Public

    🌽 Early warning yield intelligence for American agriculture — XGBoost quantile forecasting, KDTree spatial matching, and interactive Plotly dashboards on Databricks

    Jupyter Notebook