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Achievement: Pull Shark

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SharadChoudhury/README.md

💫 About Me:

I am a Senior Data Analytics Engineer at ANZ specializing in building robust data transformation pipelines and scalable ETL processes.
My expertise lies in the AWS and Hadoop ecosystems, where I leverage PySpark, SQL, Python, Hive to drive data-driven optimized solutions.

Core Tech: Python, SQL, PySpark, Kafka, Airflow and AWS (S3, Redshift, EMR).

I am currently exploring on:
GenAI & ML: Exploring RAG, LangChain, and Prompt Engineering to enhance data workflows.

💻 Tech Stack:

Apache Spark Python MySQL Apache Hadoop Apache Airflow AWS Apache Kafka InfluxDB Pandas Git Docker

📊 GitHub Stats:



Feel free to reach out via https://www.linkedin.com/in/sharadchoudhury27/.

Let's make data-driven decisions together and unlock new possibilities!

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  1. ATM-Transactions-Batch-ETL ATM-Transactions-Batch-ETL Public

    Batch ETL pipeline using Apache Sqoop, Apache PySpark, Amazon S3 and Amazon RedShift to analyze ATM withdrawl behaviours to optimally manage the refill frequency.

    Jupyter Notebook

  2. Credit-Card-Fraud-Detection Credit-Card-Fraud-Detection Public

    Credit card fraud detection of real time transaction data

    Python

  3. Hadoop-Project Hadoop-Project Public

    NYC Taxi data analysis using Mapreduce

    Python

  4. Lead-Scoring-CaseStudy Lead-Scoring-CaseStudy Public

    Scoring Leads for an Ed-Tech company to enable higher leads conversion

    Jupyter Notebook

  5. Bike-Sharing-prediction Bike-Sharing-prediction Public

    Multiple Regression model building with Sklearn and statsmodels and analysis of relevant predictors using P-values and VIF

    Jupyter Notebook

  6. Credit-EDA-Case-Study Credit-EDA-Case-Study Public

    Extensive EDA Case study of Loan applications of customers based on various factors and identifying the trends in Defaulters and Non Defaulters

    Jupyter Notebook