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Click here or scroll down to respond to this candidateCandidate's Name
Data ScientistJersey City, NJ EMAIL AVAILABLE PHONE NUMBER AVAILABLE GitHub LinkedIn SUMMARYData Scientist with over 3 years of experience in analyzing complex datasets, developing advanced machine learning models and translating data-driven insights into strategic business solutions. Proficient in statistical analysis, data visualization, and predictive modeling to optimize decision-making processes. Versatile at utilizing a diverse range of programming languages, including Python and R, along with expertise in various data manipulation and machine learning libraries. EXPERIENCEIntuit, USAData Scientist June 2023 - current Specialized in the development of Machine Learning models, resulting in a 25% improvement in efficiency, directly aligning with business objectives. Also, conducted exploratory data analysis (EDA) to uncover trends, patterns, and anomalies within large datasets, providing valuable insights to inform business decisions Leveraged NLP techniques to analyze text data and automate text classification tasks. Designed and executed A/B tests to evaluate new features and marketing strategies, optimizing user engagement and conversion rates Collaborated with cross-functional teams to define project objectives and deliver data-driven solutions. Built and maintained scalable data pipelines using Apache Spark and Hadoop, ensuring efficient processing and storage for large volumes of data Applied advanced statistical analysis techniques, such as hypothesis testing and time series analysis, to uncover correlations, causations, and trends in business metrics. Conducted the ETL processes, streamlining data extraction, transformation, and loading tasks, reducing data processing time by 30% and enhancing data accuracy Maruti Techlabs, IndiaData Scientist January 2020 - July 2022 Orchestrated the development of Deep Learning models, particularly for NLP and other relevant domains, to drive informed decision-making. Participated in all the phases of the Data Life Cycle Implemented ML algorithms, including logistic regression, XGBoost, and SVM, driving efficient model construction. Also, integrated Power BI with a plethora of data sources, automating the generation of comprehensive reports Maximized computing resources by leveraging AWS EC2 instances, ensuring scalability for intensive data processing and model training. Engineered a diverse array of models and algorithms utilizing Python and Spark for cutting-edge analytics Designed and implemented Recommendation Systems that employed Collaborative Filtering techniques, leading to a 20% increase in news recommendations accuracy for diverse users, and deployed to the AWS EMR cluster SKILLSProgramming Languages C, C++, JAVA, Python, R, JavaScript, HTML, CSS, SQL Big Data and Cloud Spark, Hadoop, Power BI, Tableau, Microsoft Excel, Kafka, AWS, GCP, Microsoft Azure Frameworks and Libraries NumPy, Pandas, Matplotlib, Scikit-learn, Seaborn, TensorFlow, ggplot2, Keras, OpenCV Tools and Technologies Git, JIRA, Docker, Linux, VScode, Postman, CUDA Database and warehouse MySQL, Microsoft SQL Server, PostgreSQL, Oracle, Big Query, Snowflake Machine Learning Regression analysis, Bayesian Method, Decision Tree, Random Forests, SVM, Neural Network, Sentiment Analysis, K-Means Clustering, KNN and Ensemble Method, CNN, NLP, LLM, Generative AI, GANs PROJECTSAI Job Application Enhancer - (React, Python, LLM) Built a Website with an AI using OpenAI Assistant API to tailor resumes and cover letters for diverse job applications Analyzed job descriptions with the LLMs to extract key skills and leveraged GPTs for natural language understanding in an intuitive interface. Engineered algorithms for resume customization and Implemented NLG for cover letter generation CorVito, A Movie Recommendation Website - (React, JavaScript, HTML, CS, NumPy) Employed the MERN stack to develop a movie recommendation website that lets users open an account and make lists of movies (from 9,000 movies) users watched and rate/review those movies The ML model developed recommends the top 10 movies, using Collaborative Filtering with GMMs EDUCATIONMaster of Science in Computer ScienceStevens Institute of Technology, Hoboken, NJ, USABachelor of Technology (BTech) in Information and Communication Technology Ahmedabad University, Ahmedabad, Gujarat, IndiaPUBLICATIONS Shah, S., Raisinghani, Y., Gandhi, N. (2022). Weighted Hybrid Recommendation System Using Singular Value De- composition and Cosine Similarity. Soft Computing and its Engineering Applications. icSoftComp 2021. Communications in Computer and Information Science, vol 1572. Springer, Cham., pp 367381 |
