Abhishek Joshi Email and Phone Number

- Led the development of a machine learning pipeline in Python to optimize package design and improve operational efficiency through root cause analysis- Created a Flask-based full stack web application for TURF analysis leveraging Flask's SQlite database for data management- Automated manual Excel processes by building Power BI dashboards, which transformed raw data into actionable insights- Built a centralized database using Python and SQL scripts to automate data collection from various sources, enhancing data management and process examination - Collaborated across teams to address ad hoc requests, utilizing data-driven analysis to deliver timely solutions and support business objectives

- Developed ETL scripts in Python with Beautiful Soup to web scrape and ensure data accuracy from various websites- Created a Tableau dashboard to visualize data reports, enhancing decision-making and reporting capabilities for the client- Conducted data wrangling and exploratory data analysis using pandas, feature engineering, and trained a predictive model with machine learning techniques, delivering analytical insights and supporting continuous improvement efforts through detailed analysis

- Conducted extensive research on YOLO Algorithm and its various advancements as a potential tool- Created a customized dataset of currency notes, and worked on its data preparation, data augmentation, and pre- processing for model usability- Developed currency detection model to identify banknotes in real-time using supervised classification techniques

- Researched and collected film industry data and automated data extraction using a web scraping script in python- Cleaned and prepared the data for analysis to create a report for displaying metrics in Power BI- Started the work on a job portal on Azure for posting and searching career opportunities in the film industry and forwarded it to the next team for subsequent steps- Documented tasks and processes for knowledge transfer to future teams and the client, detailing the framework for project planning

- Designed and implemented data pipeline architectures for multi-vendor datasets using AWS services- Extracted, cleaned, and filtered data from raw sources to load into the data warehouse- Automated report generation using data modeling in Excel/Google Sheets and Python- Used Airflow for orchestrating workflows and managing ETL processes.- Built, published, and scheduled interactive dashboards in Tableau, identifying patterns and trends in datasets- Utilized AWS Athena to analyze S3 files prior to loading them into the data warehouse- Wrote Pyspark scripts to fetch data from API calls and store it in dataframes- Strategically analyzed and communicated data to help stakeholders make data-driven business decisions- Optimized database performance, tuned queries, supported database objects, and executed stored procedures for production migration