Machine Learning Data Scientist

Vijila Yesudhas

SUMMARY

Data Specialist and Data Scientist with 2+ years of experience in data

management, analysis, correction, and advanced machine learning. Proficient in SQL, Python, PySpark, with expertise in ETL processes, data science techniques, and handling large datasets. Skilled in the Hadoop ecosystem (HDFS), JSON data management, and building machine learning models for predictive analytics. Experienced in VS Code, Google Colab, and Jupyter Notebook for development, debugging, and data analysis.

Specialized in healthcare data, particularly medical claims processing and data corrections, ensuring accuracy and compliance. Proven ability to manage high volumes of records efficiently, build predictive models, and deliver real-time insights for data-driven decision-making. Strong background in data visualization using Tableau and Seaborn.

Hands-on experience in Exploratory Data Analysis (EDA), data pre- processing, and decision tree models to analyze key customer attributes influencing loan acquisition. Recently completed hands-on projects involving advanced machine learning models and AI- driven business solutions.

EXPERIENCE

UM/CM Data Specialist

SAN ANTONIO • 02/2023 - 03/2024

● Managed high volumes of data, ensuring quality,

consistency, and accuracy.

● Collaborated with cross-functional teams to support data- related projects.

● Provided technical support and recommendations by processing claims during high-volume system transitions.

● Implemented data validation rules to ensure data reliability.

● Audited claims payment accuracy and resolved discrepancies.

● Assisted in UM/CM approvals, denials, and appeals, preparing correspondence and researching returned mail.

● Created authorization numbers and verified crucial information with medical service coordinators.

● Maintained detailed operational records, delivering insights for managerial review.

● Recognized for meeting tight deadlines and resolving data discrepancies efficiently.

PROJECTS

Personal Loan Campaign Prediction

CONTACT

**************@*****.***

210-***-****

San Antonio, TX 78254

https://www.linkedin.com/in/viji

la-yesudhas-867974262/

SKILLS

● Programming

Languages &

Libraries: SQL, Python,

PySpark, Pandas,

NumPy

● Databases:

PostgreSQL, SQL Server

● Data Formats: JSON,

Excel, CSV

● Data Management &

Analysis: Developing

ETL Pipelines, Data

Corrections, High-

Volume Data Handling

● Office Tools: Microsoft

Excel, Word, SharePoint,

Outlook

● Coding Tools: VS Code,

Google Colab, Jupyter

Notebook

● Data Visualization:

Tableau, Seaborn

EDUCATION

Post Graduate Program in AI

& ML: Business Applications

The University of Texas at

Austin

Mar-2015

Program: PGP-AIML-BA-UTA-INTL, UT Austin

● Built a predictive model to identify bank customers likely to purchase personal loans.

● Applied EDA, data pre-processing, and decision tree modeling.

● Provided insights to help the bank optimize its marketing strategies.

Tools Used: Python, Pandas, NumPy, Seaborn, scikit-learn FoodHub Analysis

Program: PGP-AIML-BA-UTA-INTL, UT Austin

• Conducted EDA to analyze restaurant demand and customer preferences.

• Delivered business recommendations to enhance customer experience and operations.

Tools Used: Python, Pandas, NumPy, Seaborn

Credit Card Users Churn Prediction

Program: PGP-AIML-BA-UTA-INTL, UT Austin

• Built classification models to predict customer churn for Thera Bank.

• Applied oversampling/undersampling to handle class imbalance.

• Conducted hyperparameter tuning to improve model performance.

Tools Used: Python, Pandas, NumPy, Seaborn, scikit-learn, XGBoost Plant Seedling Classification (CNN-Based)

Program: PGP-AIML-BA-UTA-INTL, UT Austin

• Developed a Convolutional Neural Network (CNN) to classify plant seedlings into their respective categories.

• Applied deep learning techniques for image classification. Tools Used: Python, TensorFlow, Keras, OpenCV

Stock Market News Sentiment Analysis & Summarization Program: PGP-AIML-BA-UTA-INTL, UT Austin

• Conducted sentiment analysis on financial news articles.

• Applied NLP techniques to summarize news and predict stock sentiment trends.

Tools Used: Python, NLP, NLTK, Hugging Face Transformers Diploma in Microbiology

Jul-2006

Diploma in Lab Technology

Jul-2004

CERTIFICATIONS

INTRODUCTION TO TABLEAU

Oct-2024

PYTHON FOUNDATIONS

COURSE

Sep-2024

DATA ENGINEERING

ESSENTIALS USING SQL,

PYTHON, AND PYSPARK

May-2024

.

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