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πŸ’­
Consuming data, communicating insights
πŸ’­
Consuming data, communicating insights

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commnag/README.md

Abhishek Nag

Typing SVG

LinkedIn Tableau Public YouTube Email


> SELECT * FROM me;

SELECT
    'Abhishek Nag'                                   AS name,
    'Data Scientist II, Vacation Rentals Supply Ops' AS role,
    'Expedia Group, Gurugram'                        AS based_at,
    'Causal inference, attribution, experimentation' AS works_on,
    'Claude Code + n8n pipelines that run themselves' AS tinkering_with,
    'Backend dev who fell for data'                  AS origin_story
FROM humans
WHERE curiosity > comfort
  AND coffee IS NOT NULL;

🎯 What I bring to the table

πŸ§ͺ

Causal inference
Difference-in-Differences to separate real uplift from noise

πŸ”—

Attribution
SQL logic that ties revenue back to the actions that drove it

πŸ“Š

Self-serve analytics
Scorecards and tools teams use without filing a ticket

πŸ€–

AI automation
Claude Code and n8n workflows that take the grunt work out of analysis

🧭 The journey so far

timeline
    section Education
        2016 - 2020 : B.Tech, Computer Science
                    : Guru Nanak Dev Engineering College
    section Accenture
        2020 - 2022 : Application Development Analyst
                    : REST APIs and microservices in Spring Boot
                    : Oracle SQL performance tuning
    section Expedia Group, 2023 - Present
        Data Visualisation Engineer : Supply Scorecard for leadership KPIs
                                    : Self-service conversion attribution tool
        Data Scientist II : Causal uplift with Difference-in-Differences
                          : Attribution pipeline automated with Claude Code and n8n
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πŸ” What I actually do all day (click to expand)
  • Measure what worked. Diff-in-Diff with co-treatment adjustments to estimate incremental revenue at marketplace scale.
  • Fix the numbers people argue about. Used statistical analysis to right-size attribution windows so results mature faster without rewriting history.
  • Simulate before shipping. Built a Python and PySpark simulator that stress-tests ranking logic across multiple scenarios before it reaches production.
  • Make debugging faster. Wrote a Claude-based debugging skill for attribution investigations.
  • Tell the story. Weekly, monthly and quarterly KPI reporting to stakeholder forums.

πŸ› οΈ Toolbox

Data & ML

Viz & Storytelling

AI & Automation

Engineering roots


πŸ“‚ Around this profile

Repo What's inside
danny_ma_sql_challenge Solutions to Danny Ma's 8 Week SQL Challenge
food_delivery_powerbi_dashboard Power BI dashboard answering 5 business questions for a food delivery company
super_store_excel_dashboard Excel dashboard and written report on Super Store data
pandas_bootcamp Pandas practice notebooks

More viz work lives on Tableau Public and YouTube.


πŸ“Š GitHub pulse

Popular repositories Loading

  1. super_store_excel_dashboard super_store_excel_dashboard Public

    This project consists of an excel dashboard on the Super Store data. Along with the dashboard, it tries to answer a few business problems in a report created on a separate worksheet.

    4 1

  2. commnag commnag Public

    Config files for my GitHub profile.

  3. hackerrank_python hackerrank_python Public

    This branch consists of all the code I have written for the Python problem set in Hackerrank

    Jupyter Notebook

  4. projecteuler projecteuler Public

    Jupyter Notebook

  5. emi_calculator emi_calculator Public

    This is a Python assignment with questions regarding EMI calculations. This project displays the use of numpy-financial library.

    Jupyter Notebook

  6. pandas_bootcamp pandas_bootcamp Public

    This repository contains all the practice code of pandas library.

    Jupyter Notebook