Breaking Games Externship via Extern·🟡 Open to consulting
I translate data into usable findings, with hands-on externship experience in data analytics for youth justice.
This portfolio showcases my data-cleaning, analysis, and presentation projects from my Data Analytics externship with the Center for Improving Youth Justice and other early-career experiences.
Center for Improving Youth Justice · Sep 2026 · ✅ Verified by Extern
A data analytics externship with the Center for Improving Youth Justice, focused on analyzing administrative and incident datasets to surface patterns in juvenile facility outcomes.
This project analyzes the Netflix Movies and TV Shows dataset to explore content distribution, identify trends, and generate actionable business insights. Using Python, Pandas, Matplotlib, and Seaborn, I performed data cleaning, exploratory data analysis (EDA), statistical analysis, and data visuali
I translate data into usable findings, with hands-on externship experience in data analytics for youth justice.
I’m Sonali Sankar, and I’m focused on a career in data and analysis. I completed a Data Analytics externship with the Center for Improving Youth Justice, where I transformed data into clear, actionable insights.
Externships
SQL & Database Architecture Externship with Breaking Games
In progress
Experience
Specialty Pharmacy Liaison
Caremetx LLC-Bethesda MD
Third Party Liaison
Cencora · 09/2023 – 10/2025
Patient Access Consultant
Cencora · 03/2021 – 09/2023
Senior Reimbursement Consultant
Cencora · 11/2015- 09/2016
Quality Analyst
Cencora · 11/2013 – 11/2015
Education
Montgomery College
Data Analysis Certification
Coursera
Oracle Specialization Certificate
SNDT College
Bachelor of Commerce · Class of 2000
Skills
✅ Verified by Extern
A data analytics externship with the Center for Improving Youth Justice, focused on analyzing administrative and incident datasets to surface patterns in juvenile facility outcomes.
The externship worked with CIYJ's multi‑year juvenile facility datasets, including incident reports, demographic records, and surveys. The project established analytical foundations and produced correlation-based analyses to test common assumptions about staff ratios, training, and facility outcomes. The work documented which dataset features were appropriate for correlational analysis and which
I produced an exploratory audit of the CIYJ dataset, recording variable types, missing values, and data quirks, and delivered a shared spreadsheet with exploration notes and initial cleaning suggestions.
This project analyzes the Netflix Movies and TV Shows dataset to explore content distribution, identify trends, and generate actionable business insights. Using Python, Pandas, Matplotlib, and Seaborn, I performed data cleaning, exploratory data analysis (EDA), statistical analysis, and data visuali
This project analyzes the Netflix Movies and TV Shows dataset to explore content distribution, identify trends, and generate actionable business insights. Using Python, Pandas, Matplotlib, and Seaborn, I performed data cleaning, exploratory data analysis (EDA), statistical analysis, and data visualization to better understand Netflix's content catalog.
This project demonstrates how Python in Google Colab can be used to clean, analyze, visualize, and interpret a real-world entertainment dataset. It strengthened my skills in data preprocessing, exploratory data analysis, statistical testing, and communicating findings through visualizations.
✅ Verified by Extern
A healthcare data analytics externship with TruBridge focused on analyzing public health datasets and building data products that surface patterns in infection and outcome metrics.
The externship analyzed large public healthcare datasets to identify patterns in infections and outcomes and to practice statistical and visualization techniques. The work involved building interactive dashboards, applying correlational and trend analyses, and documenting methodological limits. Deliverables included data models, visualizations, and written summaries of analytical tradeoffs.
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I validated the WHO GHO dataset for a country-year analysis by inspecting structure, variables, sample size, missingness patterns, and pairing plausibility, and concluding it met the checklist criteria for analysis.
✅ Verified by Extern · ⏱️ In progress
Turn six messy CSVs into an analytics database and a Q4 dashboard that drives real business decisions. SQL + Claude.
The project consolidated six messy CSV data sources into an analytics database and produced the data foundations for a Q4 dashboard. The work catalogued each source, mapped fields and gaps, and defined the tables and relationships required for downstream analysis.
I queried the supplied SQLite database and produced five instant answers (top products by units and revenue, product count, Meta ad spend, unique checkouts), and documented data issues including duplicated Meta tables and mismatched checkout versus referral counts.
On Project 1 I queried the supplied SQLite database, produced five instant answers (top products by units and revenue, product count, Meta ad spend, unique checkouts), noted data issues like duplicated Meta tables and mismatched checkout vs referral counts, and saved the queries and reactions in…
