Deep Mori Email & Phone Number

New Jersey, United States

-- Conceptualized, developed, and implemented a groundbreaking Data-Driven Homelessness Mitigation Platform aimed at tackling the complex challenges associated with homelessness. Leveraging a suite of cutting-edge Python technologies, this project addressed key aspects of data analytics, visualization, and predictive modeling to enhance decision-making processes and resource allocation.-- Employed Python's web scraping libraries Beautiful Soup, Scrapy to gather real-time data from various sources, including social services databases, government reports, and community outreach initiatives.-- Utilized Python's Pandas and NumPy libraries to clean, preprocess, and transform raw data into a standardized format, ensuring 14% more consistency and accuracy increased by 27%.-- Implemented geospatial analysis using Python's GeoPandas and Folium to visualize and analyze the spatial distribution of homelessness, helping identify high-impact areas for intervention.-- Implemented Spark using Scala and Spark SQL for faster testing and processing of data.-- Configured Spark streaming to get ongoing information from the Kafka and store the stream information to HDFS.-- Utilized Python's SQLAlchemy for efficient database management, ensuring seamless interaction with data repositories that helped save 12 hours of manual work per week.-- Employed Python's scikit-learn and TensorFlow to develop machine learning models for predicting homelessness trends, allowing for proactive resource allocation and intervention strategies.-- Developed interactive and real-time dashboards using Python's Dash framework.-- Ensured data security and compliance with Python's cryptography library, implementing encryption protocols to protect sensitive information and maintain privacy standards.-- Employed Docker for containerization, facilitating 37% faster deployment across variousenvironments while ensuring consistency and scalability.

Oaks, Pennsylvania, United States

-- Created Financial dashboard control panel which held the responsibility of overseeing the management, development, and design of a dashboard control panel tailored for both customers and administrators. The principal objective of this initiative was to furnish users with a comprehensive and user-friendly interface, facilitating the monitoring of their financial activities and the execution of diverse tasks.-- Apache Spark was used in processing large-scale data. It was employed for data processing, analytics, and handling complex computations while dealing with big datasets resulting in reducing the processing time by 32%.-- Python web framework Django was used for backend development. It facilitated data processing, ETL tasks, and server-side logic that led in allowing 134000 active users increased from 112600.-- Used Angular 9 reactive forms to implement complex forms and perform the validations using Form Builder. Used Angular Material components developing the UI.-- Designed various grid panels and various UI components using EXT JS and Angular.js framework and JQUERY.-- Used SQL for data retrieval, reporting, and managing the relational database.-- Worked with MongoDB, for handling unstructured or semi-structured data.-- We used Amazon S3 as the storage service for storing and retrieving large amounts of data. Amazon Redshift was also used for storing data, managing data pipelines, and performing analytical queries which helped increase the performance.-- Docker was used to package and deploy the application in a consistent and reproducible manner.-- Worked with Kubernetes to manage and scale containerized components, ensuring high availability and efficient resource utilization. It automated the deployment, and scaling of containerized applications.-- Also used PyTest to ensure the reliability and correctness of individual componentsthrough unit testing. Used Selenium and Cucumber for some part for automation testingas well.

Ahmedabad, Gujarat, India

-- Developed a data platform from scratch and participated in the requirement gathering and analysis phase of the project, documenting the business requirements.-- Worked on designing tables in Hive and MySQL using SQOOP, and processed data, including importing and exporting databases to HDFS. Involved in processing large datasets of different forms, including structured, semi-structured, and unstructured data.-- Developed REST APIs using Python and Django frameworks, and integrated various data sources, including Java, JDBC, RDBMS, Shell Scripting, Spreadsheets, and Text files.-- Worked with the Hadoop architecture and the daemons of Hadoop, including Name-Node, Data Node, Job Tracker, Task Tracker, and Resource Manager.-- Utilized AWS Data Pipeline for Data Extraction, Transformation, and Loading from homogeneous or heterogeneous data sources. Built various graphs for business decision-making using the Python Matplotlib library.-- Developed scripts to load data to Hive from HDFS and was involved in ingesting data into the Data Warehouse using various data loading techniques.

Ahmedabad, Gujarat, India

-- Designed and developed a RESTful API that linked with several third-party systems with cross-functional teams. This led to a decrease in manual data entry and a increase in data accuracy.-- Developed and implemented unit and integration tests to guarantee code quality and cut down on production issues.-- The current codebase was troubleshooted and debugged, resulting in a decrease in production issues and a increase in system stability.-- Developed Python scripts to identify SQL query vulnerabilities using permission checks, SQL injection, and performance analysis.-- Developed backend services and created many API's using Python Programming Language and SQL. -- Developed DBMS using MySQL. Involved in Agile Methodologies and SCRUM Process.