Jay Rajput

Experience: Approximately 11 months as a Research Engineer/Data Analyst with extensive experience in business and data analysis, data profiling, data migration, data conversion, data quality, data integration, metadata management services, and configuration management.

Data Handling: Skilled in handling large datasets for data cleansing, data profiling, and data scrubbing.

AWS: Good understanding of Amazon Web Services (AWS) such as AWS EC2 for computing and AWS S3 for storage.

Data Science Libraries: Proficient in data science libraries in R and Python, including NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, Seaborn, ggplot2, and TensorFlow.

Real-time Data Streaming: Experience in creating real-time data streaming solutions using Apache Spark/Spark Streaming and Kafka, and building Spark DataFrames using Python.

ETL and SQL: Extensively performed ETL operations and wrote SQL queries for data extraction, analysis, and validation.

NoSQL Databases: Proficient in utilizing NoSQL databases for real-time data processing and analytics, optimizing systems for low-latency responses.

PostgreSQL: Advanced proficiency in utilizing PostgreSQL's advanced indexing options to optimize query performance in diverse scenarios.

Excel and Power BI: Strong development experience with Advanced Excel, Power Pivot, and Power BI.

Data Visualization: Extensive experience in data visualization, including producing tables, graphs, and listings using various tools such as Tableau and Power BI.

Tableau: Proficient in utilizing Tableau's web authoring capabilities for creating and editing dashboards on the fly.

Power BI Integration: Capable of integrating Power BI with diverse data sources, including on-premises databases and cloud platforms.

Jupyter Notebooks: Knowledgeable in optimizing Jupyter Notebook configurations for resource management, maximizing computational efficiency, and minimizing processing time for large datasets.

Soft Skills: Outstanding communication and cross-cultural team management skills. Entrepreneurial attitude aimed at optimal profitability. Ambitious team leader adept at creating strategic alliances with organizational leaders and effectively aligning with and supporting key business initiatives.

• Tweet AnalysisTechnologies: Python, NLP, BERT, Deep Learning
  Data Source: Downloaded from Kaggle
  Preprocessing: Performed stemming and lemmatization
  Modeling: Used pretrained BERT model. Trained the model and achieved an accuracy of 96% using Naïve Bayes, Logistic Regression, Random Forest, and Decision Trees. Applied stacking and blending techniques on the models, achieving a blended model accuracy of 87%.
  
• Plant Disease DetectionTechnologies: Python, Computer Vision, Deep Learning
  Process: Captured photos of different crops and plants, resized them, and applied image acquisition and segmentation to isolate diseased parts of the plants.
  Accuracy: Initially achieved 94% accuracy, which was later optimized to 95.2% by adding padding and other parameters.
  Deployment: Deployed the model on the Heroku platform and integrated it into an Android app for real-life use.
  
• IMDB Movie Review PredictionTechnologies: Python, Natural Language Processing, BERT
  Data Source: IMDB dataset
  Modeling: Used BERT to predict movie reviews as positive or negative. Trained the model and achieved an accuracy of 98%.
  Deployment: Created a web app using Flask to serve the model.