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Moulik04/README.md

Hi, I'm Moulik Jain 👋

Data Science & AI Professional | Machine Learning Enthusiast | Analytical Storyteller | Pennsylvania State University

I specialize in transforming complex, multi-source data into actionable insights and predictive models. My work bridges the gap between advanced mathematical theory (Graph Theory) and real-world applications (Sports Analytics & Urban Safety) as well as between technical depth and stakeholder communication.

🏆 Course Exemplar Highlight

📘 Tableau Interactive Dashboard: Instructional Manual

  • Status: Selected as a top-tier instructional guide for beginners.
  • The Goal: To democratize data visualization by guiding novice analysts through the end-to-end process of building, filtering, and publishing interactive dashboards.
  • Key Skill: Technical Communication. I successfully translated high-level Tableau operations (Data Pane, Marks Card, Dashboard Actions) into a step-by-step pedagogical framework.

🚀 Featured Projects

⚽ Football Match Prediction (Multi-Source Data Fusion)

  • Tech: Python, XGBoost, Scikit-Learn, Pandas.
  • The Problem: Improving match outcome forecasts by combining team-level, player-level, and betting market data.
  • Insight: Mastered Entity Resolution, harmonizing naming conventions across three disparate databases, and engineered Rolling Form features that boosted model ROC-AUC to 0.78.

📍 LA Crime Visual Intelligence Dashboard

  • Tech: Tableau, Audience Analysis, Iterative Prototyping.
  • The Problem: Providing new residents with data-driven safety insights to inform housing and commuting decisions.
  • Insight: Implemented a full UX/UI workflow, from audience persona definition to iterative validation. Discovered a distinct "Noon Spike" in crime frequency through temporal analysis.

🗺️ Graph Theory & Navigation Systems

  • Tech: Discrete Mathematics, Dijkstra’s Algorithm, A*.
  • The Problem: Analyzing the mathematical optimization behind Google Maps' routing and traffic forecasting.
  • Insight: Bridged abstract math with production software. I learned to translate real-world constraints (traffic/weather) into mathematical weights in a dynamic graph.

🌿 Pribaikalsky National Park: Systems Analysis

  • Tech: Climate Data Synthesis, GIS Mapping, Socio-Ecological Modeling.
  • The Problem: Assessing the health of Lake Baikal by synthesizing 40 years of climate trends with social policy.
  • Insight: Developed Systems Thinking skills, analyzing how industrial history and overtourism interact with ecological stressors like surface water warming.

🛠️ Technical Toolkit

  • Languages: Python (Pandas, NumPy, Scikit-Learn), R (R Markdown, Tidyverse), SQL.
  • AI/ML: XGBoost, Random Forest, NLP (Intent Classification), Neural Networks.
  • Visualization: Tableau (Advanced, Interactive Dashboards, Storyboarding), Matplotlib, Seaborn.
  • Tools: Git/GitHub, Docker, Google Colab, VS Code, Excel
  • Specialties: Data Fusion, Graph Theory, AI Ethics & Fairness, Root Cause Analysis.

📫 Connect with Me

"I don't just build models; I build narratives that make data understandable and ethical."

Pinned Loading

  1. Football-Match-Prediction-Data-Fusion Football-Match-Prediction-Data-Fusion Public

    ⚽ Machine Learning pipeline using XGBoost and Data Fusion to predict European football outcomes. Features multi-source entity resolution and rolling form engineering. (0.78 ROC-AUC)

    Python

  2. LA-Crime-Data-Visual-Intelligence LA-Crime-Data-Visual-Intelligence Public

    📍 End-to-end Tableau dashboard analyzing 10+ years of LA crime data. Includes full UX research, audience analysis, and iterative design validation for urban safety.

  3. Graph-Theory-Navigation-Analysis Graph-Theory-Navigation-Analysis Public

    🗺️ Mathematical research into Google Maps' routing algorithms. Analyzes Dijkstra’s and A* applications in real-time traffic optimization and discrete networks.

  4. Pribaikalsky-Conservation-Analysis Pribaikalsky-Conservation-Analysis Public

    🌿 Multi-disciplinary systems analysis of Lake Baikal’s ecological health. Synthesizes 40 years of climate data with social policy and overtourism trends.

  5. AI-Fairness-Resume-Screening AI-Fairness-Resume-Screening Public

    ⚖️ Investigating algorithmic bias in AI-driven resume screening. Empirical testing of gender and racial bias in similarity scoring models.

  6. FC-Barcelona-Reproducible-Performance-Analysis FC-Barcelona-Reproducible-Performance-Analysis Public

    HTML