Data Scientist Machine Learning

SRI SAKTICHARAN NIRMAL KUMAR

Jersey City, NJ 201-***-**** ***.***********@*****.*** https://github.com/srisaktic/Sri_Sakti_charan_projects https://www.linkedin.com/in/sri-sakticharan/

Associate Data Scientist

Professional Summary

Motivated and detail-oriented Data Scientist with a Master’s in Data Science, strong foundations in machine learning, statistics, and analytics. Experienced in building end-to-end ML pipelines including EDA, feature engineering, model development, evaluation, and deployment. Skilled in Python, SQL, and communication of insights to both technical and non-technical audiences. Adept at working in cross-functional teams, and enthusiastic about solving real-world business problems through data.

Work Experience

ASSOCIATE SOFTWARE ENGINEER (QA Tester, Production Support) Hexaware Technologies Ltd. Feb 2022 - May 2023

Validated premium amounts, ensuring data accuracy and integrity in the environment.

Executed 100+ test cases and Optimized team productivity by 20% by tracking task progress in Excel per sprint, ensuring precise defect identification and logging in JIRA. Projects

Multimodal Phishing Detection ML + NLP + LLM (Spring 2025): Developed a phishing detection system using email messages, URLs, and images via CNN, BERT, and traditional ML models. Built hard & soft voting fusion classifiers for each modality and combined them into a unified multimodal model. Implemented Federated Learning (FL) prototype for decentralized training. Used Car Price Prediction (Spring 2024):

Developed a Random Forest model to predict BMW used car prices using 10,000+ listings. Applied data preprocessing, feature engineering, and visualization to identify key price factors. Tuned and evaluated the model using RMSE, achieving ~90% accuracy for reliable price estimation in the used car market. Fantasy Premier League Database (Fall 2024):

Engineered a fully normalized relational database (3NF) to manage FPL player stats, match history, and team records. Designed entity-relationship (ER) schema, implemented primary/foreign keys to ensure referential integrity. Developed optimized SQL queries, views, and stored procedures for seamless analytics and reporting. Implemented aggregate functions, indexing, and joins to support efficient data retrieval for complex FPL scenarios. House Sales in King County, USA (IBM Coursera):

Developed a regression model to predict house prices using feature engineering, outlier handling, and data cleaning. Built visualizations to reveal pricing trends; evaluated model with R and MSE. Skills

Programming & Libraries: Worked with Python, SQL, R, NumPy, Pandas, Scikit-learn, TensorFlow. NLP & Feature Engineering: Used TF-IDF, Word Embeddings, Tokenization, LSTM, ResNet, BERT in project work. Machine Learning: Applied Linear/Logistic Regression, Supervised & Unsupervised Learning. Visualization & Tools: Familiar with Tableau, Matplotlib, Plotly, MySQL, Jupyter Notebook, Google Colab. Soft Skills: Problem-Solving, Presentation Skills, Quick Learning, Adaptability. Certifications

Professional Data Science Certificate – Coursera IBM Education

Master of Science in Data Science (STEM)

New York Institute of Technology, NY, USA Sept 2023 - May 2025 GPA: 3.94/4.0 Key Coursework: Deep Learning, Machine Learning, Statistics, Big Data (Hadoop), Special Topics for DS (LLM, NLP). B.E. in Electronics and Communication Engineering

Anna University, Chennai, India May 2018 - June 2022 GPA: 8.17/10.0

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