Shad Patankar

Data Analytics · Python · SQL · Tableau · Risk Modeling

BBA Candidate in CIS & Data Analytics at Baruch College — building ETL pipelines, statistical models, and analytics tools across insurance, actuarial, and data science domains.

shadbusiness05@gmail.com LinkedIn GitHub

About

Turning raw data into decisions

Shad is a Data Analytics student at Baruch College with hands-on experience across insurance, actuarial, and rideshare industries, building Python ETL pipelines, statistical risk models, and interactive Tableau and Looker dashboards. He has applied machine learning techniques including decision trees and k-means clustering to real commercial datasets at Milliman, and developed actuarial pricing models as part of the Baruch Actuarial Science Society. Shad is actively seeking opportunities to apply his skills in data engineering, analytics, and risk modeling to solve high-impact business problems.

Skills

Technical toolkit

Languages & Libraries

Python (Pandas, NumPy, Scikit-learn) ●●●●●

SQL (BigQuery, PostgreSQL) ●●●●○

R (tidyverse, caret) ●●●○○

Rust ●●○○○

Analytics & BI

Tableau ●●●●●

Looker ●●●●○

Excel (VBA, Power Query) ●●●●●

Google BigQuery ●●●●○

Modeling & Methods

Statistical Modeling (GLMs) Decision Trees K-Means Clustering ETL Pipeline Design Data Warehousing Risk Assessment Loss Reserving Experience Rating Credibility Theory Probabilistic Modeling

Tools & Platforms

Git / GitHub SQLite Matplotlib Seaborn

Experience

Work & internships

Tech Talent Pipeline Apprenticeship

Tech Talent Pipeline

May 2026 – Present

Developed a Python ETL pipeline to ingest and clean real-time rideshare demand data; built interactive Tableau dashboards visualizing high-opportunity zones, contributing to a 20% increase in driver customer-acquisition speed and a 15% improvement in trip efficiency.

Data Analysis Intern

Milliman

Sept 2025 – Feb 2026

Leveraged Python, Google BigQuery, and Looker to clean, manipulate, and visualize over 10,000 commercial lines loss runs, identifying key trends in claims frequency and severity.
Applied decision trees and k-means clustering to analyze exposure data across 500 policies, providing actionable insights that informed pricing adjustments and underwriting guidelines.

Summer Intern

Aflac

July 2025 – Aug 2025

Completed 60+ hours of accredited coursework in Life, Health, and Accident Insurance.
Applied probabilistic modeling and risk assessment techniques to analyze product profitability, supporting actuarial pricing strategies.
Delivered a final presentation on findings, providing actionable insights to optimize product offerings.

AI Fellow

Headstarter AI

July 2024 – Aug 2024

Collaborated with industry leaders from Google, Meta, and Amazon in an intensive data science and programming fellowship, developing technical skills in Python, HTML/CSS, and JavaScript.
Engineered data-driven projects including automation scripts and predictive models to enhance analytical capabilities.

Projects

Selected work

NYC Air Quality

A full data warehouse with a scheduled ETL process detailing AQI and complaint relationships, with interactive visualization integration through Looker.

ETL Pipeline Data Warehouse Looker SQL

Storm Risk Project

A weather risk analysis tool that quantifies risk scores from precipitation, temperature, wind, and weather conditions, with SQLite data storage and visualizations to identify risk patterns over time.

Rust Python SQLite Data Visualization

AIG Actuarial Analyst Simulation

Analyzed 1,000+ Marine Liability claims using experience-rating techniques to calculate risk-adjusted premiums, uncovering a 12% pricing gap in high-exposure vessels.

Python Excel Experience Rating Risk Analysis

Auto Insurance Claims Model

Led a team of 4 in developing a predictive model for auto insurance claims using frequency/severity distributions to estimate loss reserves; presented to actuaries from Aon, Milliman, and Liberty Mutual as part of Baruch Actuarial Science Society.

Excel Python R Loss Reserving

Education

Academic background

Baruch College

BBA, Computer Information Systems & Data Analytics

Kips Bay, NY Graduating December 2027 GPA 3.5 / 4.0

Baruch Actuarial Science Society — Led a team of 4 in developing a predictive model for auto insurance claims using Excel, Python, and R, incorporating frequency/severity distributions to estimate loss reserves. Presented findings to judges including actuaries from Aon, Milliman, and Liberty Mutual, justifying assumptions on lapse rates and mortality tables and recommending data-driven business strategies.

Contact

Get in touch

Interested in actuarial roles. Open to full-time and internship opportunities.

shadbusiness05@gmail.com

LinkedIn GitHub 347-676-6184