SHUBH DHAR

AI Engineer & Data Scientist · AI and Information Systems at UW (GPA 3.95). Shipping production-grade GenAI and agentic systems end-to-end, backed by 2 years of industry AI engineering.

Seattle, WA

+0%

Medical device availability lift

Seawoods · AI Inventory Maximizer

+0%

User engagement rate lift

Viral Fission · Churn & engagement model

0TB+

Real-time app data managed

Azure · MongoDB · BigQuery

0.0%

Prophet forecast MAPE on PNW power prices

Energy Risk Analytics Platform

Experience

  • Led development of the "AI Inventory Availability Maximizer," an end-to-end AI resource management platform that shipped to production and lifted medical device availability by 12% through predictive modeling, automated forecast-to-fulfillment workflows, and a GenAI chat interface.
  • Built a tool-calling LLM assistant with RAG loops that let non-technical staff query inventory data, trigger forecasting tools, and retrieve fulfillment recommendations in natural language, reducing manual lookup time for clinical ops teams.
  • Designed agentic workflows around the forecasting engine so the assistant could chain data retrieval, model inference, and recommendation generation in a single conversational loop.
  • Deployed ML algorithms (Random Forests, neural networks, Gradient Boosted Trees) and a multivariate experimentation engine to drive continuous iteration on model quality.
PythonLangChainRAGTool-calling LLMsPyTorchGradient BoostingFlaskAgentic AI
  • Led AI research on Indian healthcare and financial market trends, building data pipelines with the Seeking Alpha API, storing large-scale data in PostgreSQL, and applying supervised models to predict market dynamics for faculty-led research.
  • Compared multiple supervised ML models (Random Forest, Gradient Boosting, Logistic Regression) to predict healthcare and financial company performance from online ratings, reviews, and sentiment signals.
PythonPostgreSQLSeeking Alpha APIRandom ForestGradient BoostingLogistic RegressionPandas
  • Led Viral Fission's official data platform and AI model build, shipping a churn propensity model and engagement features that lifted user engagement rate by 14%.
  • Developed a real-time data platform managing 10 TB+ of app usage data across Azure, MongoDB, and BigQuery.
  • Delivered interactive Tableau and Power BI dashboards to support product decision-making for the leadership team.
PythonAzureMongoDBBigQueryTableauPower BI

Featured Projects

  • Built an integrated decision support system using CNN-based plant disease detection, a crop recommendation engine trained on soil and weather data, and an intelligent fertilizer prediction model.
  • Shipped the full stack end-to-end: Python/Flask backend, HTML/CSS/JS frontend, MySQL database, and IoT hardware integration (Arduino Uno, Raspberry Pi, DHT11, Soil Moisture Sensors).
PythonTensorFlowKerasscikit-learnFlaskMySQLArduinoRaspberry PiIoT

Product Walkthrough

Crop & Fertilizer Prediction: The interface shows the ML model recommending 'blackgram' and '14-35-14' fertilizer based on soil NPK, pH, and environmental sensor data.

1 / 4
  • Built an AI-powered financial companion for Sound Credit Union in under 24 hours at HuskyHack 2025, featuring a RAG-based chatbot that answered user questions over their account data and a gamified financial health dashboard with life-event detection.
  • Shipped the full experience end-to-end — chat-driven loan analysis (e.g. parsing a $1M Lamborghini ask into payment + APR scenarios), cross-bank account optimization, a 0–100 financial health score with Level/XP gamification (Savings Rate, On-Time Payments, Budget Usage sub-scores), achievement unlocks (Budget Master, Savings Streak, Reward Hunter, Bill Ninja), 6-month income vs. expenses + savings-progress charts, and life-event detection that surfaces contextual recommendations (auto-loan pre-qual at 3.2% APR, multi-lender rate compare, credit-score uplift, monthly budget impact) — then presented to Sound Credit Union stakeholders.
RAGLLMReactFinancial AnalyticsGamification

Product Screenshots

SoundGuide AI chatbot analyzing cross-bank benefits alongside proactive notifications. Bill reminders, low-balance alerts, and savings milestones.

1 / 5
  • Built an end-to-end electricity market risk analytics platform with a Python/Plotly Dash dashboard covering market analytics, VaR/CVaR risk metrics, price spike detection, and counterparty credit scoring across 15 counterparties (A/BBB/BB ratings).
  • Developed an R-based ARIMA/Prophet 90-day forecasting module on Pacific Northwest Mid-Columbia Hub prices (Prophet MAPE 25.9%, RMSE $16.04/MWh).
PythonPlotly DashRARIMAProphetVaR/CVaRTime Series

Dashboard & Model Previews

Market Overview: Mid-Columbia Hub wholesale electricity prices, 2022–2024, with Bollinger Bands, 30-day rolling mean, and automatic price spike detection.

1 / 4

Education

University of Washington

MS Information Management, Data Science & AI Engineering

GPA 3.95

Sep 2025 – Present

University of Mumbai

BTech Information Technology

GPA 3.7

Aug 2019 – Jul 2023

IBM

4-year AI Engineering Certification

GPA 3.75 · Top 10%

IBM AI Digital Badge

Skills

GenAI & Agentic Tools

Claude CodeCursorReplitLovableGPTGeminiObsidian

GenAI Coding

LangGraphLangChainLlamaIndexOpenAIAWSGemini

AI & Software

PythonTensorFlowPyTorchscikit-learnPandasNumPyRAGFlaskDjangoNode.jsJavaScriptJavaC++C#.NETSwift

Data & BI

SQLMongoDBBigQueryDatabricksGCPAWSPower BITableauGoogle AnalyticsA/B Testing