Skip to content
View manish-kr0722's full-sized avatar

Block or report manish-kr0722

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
manish-kr0722/README.md

Manish Kumar

Banking experience • SQL • Power BI • Excel • Python

I am a banking professional transitioning into Data Analytics, with over three years of experience at ICICI Bank and HDFC Bank and a B.Tech in Computer Science.

My portfolio demonstrates SQL analysis, Power BI reporting, Python data preparation and interactive Streamlit applications. I focus on explaining the business question, validating the data and communicating findings alongside their limitations.

Selected projects

Project Business focus Tools Evidence
Bank Customer Churn Analysis Customer retention and churn patterns SQL, Python, Power BI 10,000 customers; 20.37% observed churn
Global Superstore Sales Sales and profitability reporting Power BI Two-page dashboard; documented 11.61% profit margin
HR Attrition Dashboard Workforce composition and attrition Power BI, SQL, Python 1,470 fictional employee records
Credit Risk Analysis Borrower affordability and recorded loan outcomes Python, Power BI Data preparation, exploratory analysis and baseline modelling
Facebook Live Sellers Content engagement and post segmentation SQL, Python, Power BI Reactions, comments and sharing patterns

Interactive applications

Skills demonstrated in this portfolio

  • SQL: aggregation, joins, CTEs, subqueries and window functions.
  • Power BI: interactive reports, KPI presentation, filters and page navigation.
  • Python: Pandas, NumPy, Matplotlib, Seaborn and scikit-learn.
  • Interactive reporting: Streamlit and Plotly.
  • Analysis: data cleaning, exploratory analysis, customer segmentation and business reporting.

Professional background

My banking experience includes customer and account data management, Excel-based reporting, sales performance tracking and coordination with internal teams. My technical analytics experience is demonstrated through independent and course projects.

I am seeking Data Analyst opportunities, particularly in banking, business reporting and operations analytics.

Additional learning project

Netflix Recommendation Prototype explores collaborative filtering. Its README documents the current reproducibility and movie-metadata limitations.

Connect

LinkedIn · Email

Pinned Loading

  1. bank-customer-churn-analysis bank-customer-churn-analysis Public

    Bank customer churn analysis using SQL, Python and Power BI, with segment findings and baseline model comparison.

    Jupyter Notebook

  2. Credit-Risk-Analysis Credit-Risk-Analysis Public

    Exploratory loan-risk analysis using Python and Power BI, including borrower comparisons and classification results.

    Jupyter Notebook

  3. Global-Superstore-Sales Global-Superstore-Sales Public

    Power BI dashboard analysing sales, profitability, products, customer segments and geographic performance.

  4. hr-attrition-dashboard hr-attrition-dashboard Public

    Workforce attrition analysis using fictional IBM data, with Power BI dashboards, SQL and Python.

    Jupyter Notebook

  5. fitness-analytics-streamlit fitness-analytics-streamlit Public

    Interactive Streamlit dashboard exploring Fitbit activity, sleep, hourly movement and data quality.

    Python

  6. mental-health-analysis mental-health-analysis Public

    Workplace mental-health survey analysis with Python data cleaning, exploratory analysis and Streamlit reporting.

    Jupyter Notebook