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Click here or scroll down to respond to this candidateCandidate's Name
Research_Lab_Team PHONE NUMBER AVAILABLE EMAIL AVAILABLE LinkedIn medium/Candidate's Name GitHub EDUCATIONSyracuse University Syracuse, NYMaster of Science Applied Data Science (GPA: 3.8) Aug 2021 May 2023 Relevant Coursework: Machine Learning, Quantitative Statistics and Reasoning, Data Visualization, AWS Academy Cloud Foundations. Birla Institute of Technology and Science Pilani Hyderabad, India Bachelor of Engineering (Honors)- Electronics and Instrumentation Aug 2014 Jul 2018 Relevant Course Work: Object Oriented Programming, Principles of Management, Human Resource Development. TECHNICAL SKILLSProgramming Languages: Python, R, SQL, PLSQL, JavaScript, Java, Shell, OWL, RDF, SPARQL. Software Tools: Rally, JIRA, Figma, IBM- BPM, Jupiter, Power BI, Excel, Oracle SQL, ServiceNow, RStudio, Protg. Software Packages: TensorFlow, Scikit-learn, NumPy, py-mining, spacy, seaborn, NLTK, REGEX, QUEPY. PROFESSIONAL EXPERIENCEDeveloper/ Research Assistant, C4 Labs, Syracuse University Oct 2023 Jun 2024 Developed an application to search and find the desired records from terabytes of reddit data with Python. Researched on the differences in biases between LLM ChatGPT, Llama by identifying polar user groups and generating data from the LLMs. Later, we calculated how far apart were the data generated was from polar user groups by their vectorial representation of data. Data Scientist, Keck Medicine, University of Southern California Jul 2023 Oct 2023 Coordinated with leadership, resident advisors, and surgeons to optimize analysis of EHR data in Cerner. Scripted code in python to classify and display clinical staging events of Surgery Data on Qlik sense. Extracted, Transformed, and Loaded data from the Cerner database to a new data architecture and removed discrepancies in the EMR records of surgeries between different data sources. Performed data analysis and visualization to analyze the performance of the Department of Surgery regarding surgeon and type of surgeries. Associate Consultant, Capgemini Sep 2018 Jul 2021 Developed SQL batch job triggers and database backend for a cloud application for 13 banking applications. Project Management of 13 banking applications handled by prioritizing items list of user stories and production issues in Rally and JIRA. Executed Change Management and validated 20+ deployments, acting as a liaison for Middleware Ops, DevOps, and Database teams, ensuring compliance with best practices. Monitored the status of deployed applications before and after deployment, incorporating security measures, and gathered feedback on UAT (user acceptance testing) from clients, fostering communication and optimization. PROJECTSGravity Spy, Zooniverse NSF( HCC Grant 21-06865 ) Jan 2022 - Aug 2022 Collected historical trace data of various Users from the Zooniverse website and cleaned the data to ensure data accuracy and completeness. Feature Engineered 7 million rows of time series trace data to form sequences of activities and calculated the TFIDF score of sequences. Created a Semantic Data Architecture to group 70k users in accordance with their performance. Employed Decision Trees with Python to analyze those sequences and designed a model to find potential high performing users. Improved the performance of users by recommending analytical findings from sequences of high-performance users. Collaborated with other researchers on FIGMA for designing UI and enhancing user experience with JavaScript. Drug Inventory Analysis Jan 2022 - Apr 2022 Performed Churn Analysis on the Inventory of Pharmaceutic Drugs. The drugs were classified by Machine Learning based on rating and its respective features, for example, number of times a review of the drug was useful for a patients symptoms. Conducted EDA from ML techniques like clustering and associative mining. Created Decision Trees classifier to obtain the maximum performance in classifying the rating of the drug from the symptom associated. Built Natural Language Classifiers and compared the performance and accuracy of Decision Trees, Max Entropy and Naive Bayes. Transformed text reviews via glove embedding. Pre-pruned nave bayes model to predict rating of drugs from text reviews. |
