Data Analytics • Machine Learning • Transit Operations

Turning operational data into reliable decisions.

I’m Chinmay Naringrekar, a data analyst at MTA focused on transit reliability, forecasting, dashboards, and machine learning projects that connect analytics with real-world operations.

4+ yrs Analytics experience
ML + BI Python, SQL, Power BI
MTA Transit operations analytics

Machine Learning Projects

Selected work combining real-world data, forecasting, recommendation systems, generative AI, and explainable analytics.

OTP Forecasting

[WIP]Staten Island OTP Forecasting

End-to-end machine learning project using MTA open data to forecast on-time performance, compare models, and explain predictions using SHAP.

Python XGBoost SHAP Streamlit

F1 Strategy ML

[WIP]F1 Pit Strategy and tyre degradation ML Project

Formula 1 race analytics and machine learning project using FastF1 to analyze Monaco 2025 race pace, tyre degradation, and lap-time prediction.

Python FastF1 Pandas Race Analytics

K-Drama Recommender

K-Drama Analytics & Recommendation System

Personalized recommendation and analytics app built from drama metadata and personal ratings to analyze taste profile and suggest new shows.

Python Pandas NLP Streamlit

PDF QA Chatbot

PDF QA Chatbot with RAG

Generative AI app that lets users ask questions about uploaded PDFs using document chunking, embeddings, FAISS similarity search, and LLM responses.

LangChain FAISS OpenAI RAG

Decision Tree

Breast Cancer Decision Tree Model

Machine learning assignment using cell nuclei features to train, test, evaluate, and visualize a decision tree classification model.

Scikit-learn Classification Confusion Matrix Model Evaluation

Healthcare ML

Disease Progression ML Project

Planned healthcare analytics project focused on disease progression, multimorbidity patterns, risk prediction, and clinical decision-support storytelling.

ML EHR Data Classification Explainability

Dashboards

business intelligence and visualization projects from my earlier portfolio, including Tableau and Excel dashboard work.

Seattle Airbnb

Seattle Airbnb Tableau Dashboard

Tableau dashboard analyzing Seattle Airbnb listings to understand rental patterns, pricing factors, and strategy for optimizing short-term rental decisions.

Tableau Airbnb Pricing Analysis BI

Netflix

Netflix Tableau Dashboard

Interactive Tableau dashboard exploring Netflix titles by type, country, rating, genre, release year, and detailed movie/TV show information.

Tableau Entertainment Data Maps Visual Analytics

Spotify

Spotify Top Tracks Dashboard

Dashboard analyzing Spotify top tracks using song attributes such as key, acousticness, instrumentalness, danceability, valence, energy, and streams.

Tableau Music Data Trend Analysis Dashboard

COVID-19

COVID-19 Tableau Dashboard

Tableau dashboard built after SQL exploration of global COVID-19 data, showing death percentage, infection rates, continent-level death counts, and projected trends.

SQL Server Tableau Public Health Forecast View

COVID-19

COVID-19 SQL EDA

SQL exploration of global COVID-19 data, showing death percentage, infection rates, continent-level death counts, and projected trends.

SQL Server Tableau Public Health Forecast View

Bike Buyers

Bike Buyers Excel Dashboard

Excel dashboard using cleaned customer data to identify factors influencing bike purchases, with interactive filters and business-focused visual summaries.

Excel Dashboard Data Cleaning Customer Analysis

Skills

A mix of analytics, machine learning, business intelligence, and operational reporting tools.

Data Analysis

Excel, SQL, Python, pandas, exploratory analysis, KPI tracking, and operational reporting.

Machine Learning

Regression, classification, model evaluation, forecasting, XGBoost, scikit-learn, and SHAP.

Dashboards

Power BI, Tableau, Streamlit, executive dashboards, monthly reports, and performance visuals.

Data Systems

SQL Server, Oracle, Trino, AWS S3, Redshift, Athena, and data pipeline organization.

Analytics built for real-world operations.

My work focuses on converting messy operational data into clear insights, dashboards, forecasts, and decision-support tools. I’m especially interested in reliability analytics, predictive maintenance, and explainable machine learning.

I’m currently expanding my portfolio with projects that connect business intelligence, machine learning, and practical operational decision-making.

  • Transit reliability and performance analytics
  • Forecasting and explainable machine learning
  • Dashboard development for leadership and operations
  • Data storytelling with measurable business impact

Let’s connect.

I’m interested in analytics, machine learning, business intelligence, and decision-support projects — especially where data can improve operational performance and reliability.