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                                              Candidate's Name
                          Boston, MA | PHONE NUMBER AVAILABLE | EMAIL AVAILABLE | LinkedIn | GitHub
                            Seeking Full-Time Data Engineering Opportunities starting June Street Address
EDUCATION
Northeastern University                                                                                    Boston, Massachusetts
Master of Science in Information Systems                                                                             May Street Address

Vivekanand Education Society s Institute of Technology                                                            Mumbai, India
Bachelor of Engineering in Electronics Engineering                                                                   May 2020

EVIDENCE OF EXCELLENCE
  Created dynamic dashboards using Power BI and Tableau, facilitating executive-level decisions
  Managed and optimized data storage across MySQL, Spark, and AWS for large-scale projects
  Developed over 5 complex ETL/ELT pipelines using Python and Airflow, optimizing data workflows
  Implemented 5+ machine learning models using TensorFlow and Keras, contributing to predictive analytics solutions
  Led training sessions on Python, Power BI, Tableau, ELK Stack, and SQL for new hires

EXPERIENCE
National Stock Exchange Information Technology                                                                    Mumbai, India
Data Analyst                                                                                       March 2021   December 2021
  Developed and delivered over 50 BI Publisher reports and 5 integrations on financials modules, streamlining financial reporting
    and enhancing data-driven decision-making
  Optimized BI Publisher code performance by 50% through query optimization, redundant table call elimination, and pre-
    execution WITH clause implementation, significantly improving data analysis efficiency
  Automated the extraction and visualization of over 200GB of monthly examination data using SQL and Power BI, reducing the
    time to insights by 50% and enabling stakeholders to make better decisions
  Designed, implemented, and managed Airflow orchestration for top clients, enabling real-time monitoring of system events in
    critical internal applications by performing log analysis
  Developed and deployed a machine learning pipeline to process 20 TBs of daily stock data using Apache Spark to identify trader
    outliers, achieving 90% better accuracy than prior methods
  Developed a data pipeline to detect instances of cheating among students using Python and Tableau, automating data analysis and
    reporting, saving over 10 hours of manual work each week and enhancing academic integrity
  Conducted training session for new hires on Python, Power BI, Tableau, ELK Stack and SQL, enabling new employees to
    contribute effectively to data-driven initiatives
PROJECTS
Iowa Liquor Sales
  Extracted data from Google BigQuery and Iowa government website, creating a robust 26 million record dataset for analysis
  Performed comprehensive data profiling using Alteryx to identify and address anomalies, ensuring data integrity and accuracy
  Built a dimension model containing 8-dimension, 4-fact table in Navicat for enhanced query performance and data organization
  Developed a robust data pipeline using Alteryx and designed visually compelling interactive dashboards and reports in Power BI
   to effectively communicate insights derived from the analysis
Traffic Sign Recognition
  Executed traffic sign recognition project using SVM, Random Forest, CNNs, and Scikit-Learn's MLP Classifier
  Conducted Exploratory Data Analysis (EDA) on the German Traffic Sign Recognition Benchmark dataset, gaining insights into
    data distribution, class imbalances, and visualizing feature relationships
  Analyzed custom CNNs vs. VGG-16 transfer learning, evaluating accuracy, loss, and applying regularization for optimization
  Attained outstanding CNN model results using SGD and Adam optimizers: 89.31% and 95.63% accuracies. Top Random Forest:
    79.66% accuracy; SVM: 83.00% accuracy
Heart Failure Prediction and Analytics
  Led team in employing 9 ML algorithms for precise heart condition prediction, enhancing healthcare and diagnoses
  Applied rigorous hyper-parameter tuning to promote generalization, mitigate overfitting, and bolster model accuracy
  Leveraged ensemble learning's Stacked algorithm to create a potent predictive model
  Random Forest emerged as the leading performer, showcasing exceptional result of 85.81%, while the Stacking Classifier closely
   trailed to 84.42%, reinforcing the efficacy of the ensemble approach

SKILLS
Programming Languages: Python, Advanced SQL, Java, HTML, C, C++
Data Engineering and Data Visualization: Talend, Alteryx, Airflow, Informatics, Power BI, Tableau, Elasticsearch, Apache Spark
Data Science and Machine Learning: NumPy, Pandas, Matplotlib, scikit-learn, TensorFlow, OpenCV, Pytorch, Seaborn, Keras
Cloud Services: AWS S3, GCP, Azure Data Factory, Databricks, Lambda