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Candidate's Name
Chicago, IL +1(Street Address )470-3892 EMAIL AVAILABLE LINKEDIN LINK AVAILABLE https://github.com/jitendra3010 EDUCATIONMaster of Science in Data Science 01/2023 - 11/2024 DePaul University, Jarvis College of Computing and Digital Media GPA: 4.00/4 Bachelor of Technology in Information Technology 03/2005  03/2009 Biju Patnaik University of Technology, National Institute of Science and Technology GPA: 3.46/4 SKILLSTechnical Skills: Python, R, Java, SQL, PL/SQL, MySQL, PostgreSQL, JSON, Machine Learning, Supervised and Unsupervised Learning, Predictive Modeling and Analysis, Data Analysis and Regression, Data Regularization Techniques, Hadoop, MapReduce, ETL, EDA, Convolutional Neural Network (CNN), Deep Learning. Framework/Libraries: J2EE, Spring, Oracle Application Development Framework (ADF), SCRUM, OpenCV, Pillow, PyTorch, TensorFlow, scikit learn, NumPy, SciPy, pandas, matplotlib, seaborn, ggplot, Pyplot, Plotly. Tools: REST Services, AWS, Microsoft Azure, Oracle Cloud, Power BI, Tableau, JIRA, ServiceNow, Microsoft Office, R-studio, Jupyter notebook, Visual Studio, eclipse, VSCode, IntelliJ, Postman, Soap UI, Rest API, GIT, SVN, Jira. Other: Agile, Dashboard development, Data Engineering and Modeling, Data Manipulation, Cloud Computing, ETL Processes, Statistical problem solving, innovative thinker, critical thinking, analytical skills, client handling. EXPERIENCEMachine Learning Research Analyst 01/2024 to Present DePaul CoBaab Lab, Chicago, IL Spearhead controlled experiments to evaluate the effectiveness of machine learning models in detecting fractures and edema. Developed and iterated analysis pipelines using Python and PyTorch to enhance the accuracy and efficiency of CNN models with optimized U-net architecture for medical imaging, resulting in a 75% accuracy in bounding box identification for edema detection. Data Scientist 06/2023 to 09/2023DePaul CoBaab Lab Chicago, IL Performed advanced analytics on complex dataset of mice brain, to uncover insights in gene expression studies. Developed and implemented statistical and machine learning models utilizing PCA for dimensionality reduction and advanced visualization techniques with Matplotlib and Seaborn, leading to enhanced data-driven decision-making. Principal Application Engineer 05/2014 to 11/2019Oracle Hyderabad, India Spearhead a team in adopting Agile methodologies, enhancing project efficiency and delivering impactful software solutions Automated reporting processes developed dashboards to provide insights at scale which saved 1.5 hr. of manual effort every day. Spearhead the development of data-driven solutions for Oracle Cloud Services, implemented RESTful web services for all domain DB components in ADF, tested using Postman with OAuth2 security principles for user data protection. Increased revenue by 10% through the successful deployment of a B2B messaging solution, driving significant business impact. Executed comprehensive Unit, Integration, Performance, and Regression testing, utilizing libraries like JUnit ensuring 100% code coverage and reducing errors and downtime.Technology Analyst 06/2009 to 05/2014Infosys Hyderabad, India Built data analysis pipelines and conducted statistical analysis to support key financial decisions for clients like BOFA and AMEX. Spearhead a PL/SQL-driven data solution through an ETL process of over 5 million records, Improved operational efficiency by 70% through performance tuning and SQL query optimization techniques. Developed web applications and data repositories, reducing costs and improving efficiency through automation and optimization. PROJECTS Lane and Curve Detection for Autonomous Vehicles: Created a real-time image processing pipeline for lane detection, utilizing OpenCV and deep learning models to enhance autonomous vehicle navigation. Movie Recommender System: Built a recommendation system with regression and classification for predicting revenue and success; utilized content-based and collaborative filtering (SVD) for recommendation. Gesture Recognition with Hybrid 3D Pooling CNN: Designed a gesture recognition system using a hybrid 3D pooling CNN, achieving high accuracy in low-resolution environments with neural network and deep Learning Techniques for smart TV. Facebook Interaction Dataset Analysis: Analyzed post metrics to predict performance with a MAPE of 6.0%, informing post publication strategies with regression models. Heart Attack Analysis and Prediction: Developed a predictive model for heart attack likelihood with an accuracy of 84%, using advanced machine learning techniques and statistical analysis.