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Click here or scroll down to respond to this candidateEDUCATIONCandidate's Name
USA EMAIL AVAILABLE PHONE NUMBER AVAILABLE LinkedInMaster of Science in Data Science -- University of North Texas, USA Aug 2022 - May 2024 Courses: Applied Machine Learning, Computational Linguistics, Data Visualization, Fundamentals of Data Analytics, Data (GPA: 3.7/4) Mining and Knowledge Discovery, Data Modeling, Data Visualization, Principles and Techniques for Data Science. TECHNICAL SKILLSProgramming Languages: Python, PySpark, SQL, SAS, HTML Libraries: Pandas, NumPy, Matplotlib, Feature Modeling, Plotly, Scikit-learn, Seaborn, Scipy, NLTK, Tensorflow, Keras, PyTorch, OpenCVData Science: Statistics, Probability, A/B Testing, Hypothesis Testing, Time Series Data Visualization: Tableau, Power-BI, Excel, Trifacta, SAS Visual Analytics Tools: JIRA, Trello, Flask API, Juptyer Notebook, Google Colab, Visual Studio Code ML Techniques: Supervised, Unsupervised, Regression Analysis, Classification, Decision Trees, Clustering, LightGBM, Random Forest, Neural Networks (ANN, CNN, RNN), Transformers, Ensemble Models (XGBoost, Bagging), NLP, LSTM.Azure Tools: Azure Data Factory, Azure Data Bricks, Azure Data Lake Storage Azure Synapse, Azure ML Studio. ML Models & Metrics: BERT, GPT, BARD, Gemini, ROC, AUC, F1 Score, Heat Map, Precision, Recall. Data Engineering: Azure, Snowflake, Airflow, Docker, Data Warehousing, Linux, Spark Other: Reporting and Documentation, Effective communication, Fast-learner, Problem-solving, Time Management PROFESSIONAL EXPERIENCEjGRADUATE ASSISTANT (DATA ANALYST) -- UNIVERSITY OF NORTH TEXAS, USA Aug 2022 May 2024 Data-driven insights: Crafted captivating reports and floor heatmaps visualizing student enrollment, course trends, and campus engagement. Impactful action: Analyzed underperforming programs to launch outreach campaigns, boosting crucial course enrollment by 8%. Empowered decisions: Built 9 interactive dashboards for real-time tracking of enrollment, performance, and engagement, guiding data driven. Skills Developed: Tableau, Power BI, Microsoft Excel, SAS Visual Analytics, SQL AUDIT AND ASSURANCE ANALYTICS SENIOR SPECIALIST -- DELOITTE, INDIA Aug 2020 Aug 2022 Streamlined audit processes and delivered actionable insights for auditors through data-driven automation and visualization with a proven track record building and handling end to end projects and worked in a fast-paced collaborative environment with continuous improvement. Clean & prep: Masterfully wrangle messy data using Excel macros and Access DB for rapid analysis. Data Wrangling: Processing massive datasets using Trifacta for 30% faster analysis for several customers. Automated Reconciliation: Automated Trial Balance & General Ledger reconciliation with SAS, saving clients 10% review time. Delivered detailed reports pinpointing discrepancy patterns for deeper analysis. Visual storytelling: Crafted Tableau dashboards, pinpointing anomalies, and potential discrepancies through advanced data visualization. Gained recognition from senior management for displaying exemplary performance and got awarded with Spot awards in April 2021 & Jan 2022. Skills Developed: Tableau, SQL, Microsoft Excel, VBA, SAS, Trifacta, MS Access DB, Reporting and Documentation MACHINE LEARNING ENGINEER -- HIGHRADIUS, INDIA July 2019 - July 2020 Streamlined B2B deductions with ML expertise and built & deployed Dispute Validity Prediction model with a 95% accuracy rate. Reduced review time by 20% for high-volume dispute cases.Skills Developed: Classification, LightGBM, XGBoost, Pandas, NumPy, Matplotlib, Scikit-learn, Seaborn, Scipy, SQL, Jupyter Notebook. SUMMER INTERN -- HIGHRADIUS, INDIA May 2019 - June 2019 Designed an AI-Enabled B2B Fin-Tech Cloud Application per the organizational requirements. Skills Developed: Python, SQL, HTML, Machine Learning Algorithms, Jupyter Notebook, SQLPROJECTS Income Qualification: Developed an ML model using random forests to predict poverty levels in Latin American households with 96% accuracy, exceeding established benchmarks and paving the way for improved resource allocation by social programs. Cardiovascular System: Leveraged weighted voting classifier ensemble to achieve 87% accuracy in predicting cardiovascular disease, outperforming individual models, and surpassing benchmarks for early diagnosis support in resource-limited settings. Face Detection: Implemented OpenCV and Dlib in Python to build a real-time face detection and counting system, focusing on bounding box accuracy rather than facial feature extraction.CERTIFICATIONS Introduction to Machine Learning By NPTEL, IIT KGP, October 2018 |
