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Achievement: Pull Sharkx2

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Achievement: Pull Sharkx2

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alangudi417/README.md

Hi there, I'm Alan! 👋

I come from a Business Analytics background with experience in pricing strategy, reporting, and operational analytics, now turning to Data Scientist. I enjoy solving complex problems using data, statistics, and machine learning. Passionate about transforming data into actionable business insights.

Some key things about me

  • 📊 Strong focus on Exploratory Data Analysis (EDA) and ETL processes
  • 🤖 Currently expanding skills in Machine Learning and Predictive Modeling
  • 💼 Business-driven mindset with experience translating business needs into data solutions
  • 🌎 Open to remote and international opportunities

⚡ Tech Stack

Programming & Data

  • Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn)
  • SQL (MySQL, SQLite)

Data Visualization & BI

  • Power BI
  • Excel (Advanced + VBA)

Data Science & Analytics

  • Exploratory Data Analysis (EDA)
  • ETL & Data Cleaning
  • Statistical Analysis
  • Feature Engineering
  • Predictive Modeling

Business & Systems Tools

  • Salesforce (CRM)
  • SAP (ERP)
  • Jira

Pinned Loading

  1. videogames-sales-success videogames-sales-success Public

    Data analysis project using EDA and statistical testing to identify commercial success factors in global video game markets.

    Jupyter Notebook

  2. industrial-gold-recovery-prediction industrial-gold-recovery-prediction Public

    Machine learning pipeline for predicting industrial gold recovery, optimizing process efficiency using sMAPE and ensemble regression models.

    Jupyter Notebook

  3. oil-well-profitability-model oil-well-profitability-model Public

    Machine learning and risk simulation project to identify the most profitable oil drilling region using predictive modeling and bootstrapping

    Jupyter Notebook

  4. telecom-prepaid-plans-revenue telecom-prepaid-plans-revenue Public

    Data analysis project using EDA and statistical testing to identify revenue drivers and profitability differences between Megaline prepaid plans.

    Jupyter Notebook

  5. online-groceries-customer-behavior online-groceries-customer-behavior Public

    Data analysis project using EDA and relational datasets to uncover customer purchasing patterns and product demand drivers in online grocery retail. Includes real-world data cleaning, behavioral se…

    Jupyter Notebook

  6. ride-sharing-demand-analysis ride-sharing-demand-analysis Public

    Data analysis for Ride-sharing market and demand analysis for Chicago, integrating trip, competitor, and weather data to generate data-driven operational and strategic insights.

    Jupyter Notebook