Data Scientist

Leveraging 4+ years of experience in software development and data science to build impactful machine learning models and derive actionable insights.

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About Me

Data Scientist with 4+ years of experience in software development and data science, with a Master’s in Computer Science (Specialization in Data Analytics). Proven expertise in developing and deploying machine learning models, building interactive dashboards, and deriving actionable insights from large-scale datasets. Adept at predictive modeling, fraud detection, risk analysis, time series forecasting, and natural language processing. Looking to leverage both software engineering and advanced analytics skills in data-driven roles within the finance, banking, or tech sectors.

Technical Skills

Languages & Tools

Python

SQL

Java

Jupyter Notebook

Google Colab

Git

PyCharm

VS Code

Libraries & Frameworks

NumPy

Pandas

Scikit-learn

TensorFlow

Keras

Matplotlib

Seaborn

PySpark

NLTK

Data Science & ML

Supervised & Unsupervised Learning

Deep Learning

NLP

Computer Vision

Time Series

Clustering

Regression

Classification

Model Evaluation

Feature Engineering

Regression Modeling

Business Forecasting

Data Engineering

ETL

Data Wrangling

APIs

SQL Optimization

Relational Databases

Visualization & Cloud

Tableau

AWS (S3, EC2)

Linux

Professional Experience

Graduate Assistant – Application Developer

University of Illinois at Springfield - Springfield, IL

Jan 2024 – Present

Developed full-stack, data-driven web applications improving workflow automation and reducing manual workload by 40%.
Designed a Car Rental Web App with integrated analytics, saving $30K annually by removing third-party dependencies.
Created the Research Connections platform, increasing student participation by 30% and streamlining data collection.
Applied data analytics techniques to optimize query performance, reducing page load times by 20% and improving scalability by 35%.
Built dashboards using Tableau to track usage metrics, performance KPIs, and error rates.

Software Engineer

Seamless Distribution Systems - Mumbai, India

Dec 2022 – Jan 2024

Developed fraud detection models using Isolation Forest, Random Forest, and Logistic Regression, reducing fraud-related losses by 20%.
Implemented AES 256-bit encryption and anomaly detection systems using ML for real-time monitoring of recharge activity.
Built end-to-end machine learning pipelines for secure, scalable telecom voucher systems, boosting throughput by 60%.
Deployed interactive fraud-monitoring dashboards in Tableau for anomaly tracking and risk profiling.

Full Stack Developer

Azeus Convene India Pvt. Ltd. - Noida, India

Jun 2022 – Nov 2022

Enhanced backend performance and optimized database queries for secure, scalable paperless solutions, increasing system speed by 30%.
Integrated collaborative analytics features to boost client engagement by 40%.
Applied SQL analytics and backend scripting to deliver real-time reporting and usage pattern visualization.

Senior Software Engineer

Comviva Technologies Pvt. Ltd. - Gurugram, India

Aug 2020 – Jun 2022

Designed scalable backend services for high-volume telecom operations for clients such as Jio, Vodafone Idea, and Ooredoo, ensuring seamless service delivery to millions of users.
Implemented real-time recommendation systems using behavioral and usage data, increasing caller tune engagement and driving revenue growth.
Leveraged data analytics to uncover usage trends, reduce churn, and enhance platform stability across multi-regional deployments.
Built monitoring dashboards in Tableau to visualize service uptime, customer behavior, and system performance.
Recipient of the Comviva Credo Cap Award for Excellence (2021–2022) for outstanding contributions to system optimization and client satisfaction.

Academic Projects

Fraud Detection System

Built real-time fraud detection pipelines using Isolation Forest and Random Forest, improving anomaly detection accuracy by 25%. Deployed fraud dashboards using Tableau for transaction-level monitoring and compliance tracking.

Technologies Used:

Isolation Forest

Random Forest

Tableau

Python

View Code

Customer Segmentation & Personalization

Applied K-Means, RFM Analysis, and Hierarchical Clustering on customer data to identify segments and improve targeting. Visualized engagement metrics and KPIs in Power BI dashboards, improving campaign ROI by 15%.

Technologies Used:

K-Means

RFM Analysis

Hierarchical Clustering

Power BI

View Code

Predictive Analytics for Risk and Performance

Developed credit risk models using financial indicators and macroeconomic variables; reduced loan default rates by 20%. Created real-time dashboards for tracking risk scores, model performance, and historical trends.

Technologies Used:

Machine Learning

Risk Modeling

Dashboarding

Python

View Code

Sales Forecasting & Demand Prediction

Built forecasting models using ARIMA, XGBoost, and Prophet for product demand prediction. Delivered insights through dynamic dashboards with seasonal indices and resource planning recommendations.