Available for opportunities

Aditya Kumar Data Analyst, turning data into decisions.

SQL · Power BI · Excel · Python — I build dashboards, automation tools, and analyses that move metrics. Currently turning 10K+ assets into actionable insight at Cityfurnish.

Dashboards shipped

Records cleaned

Defaults reduced

View my work→ Get in touch

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01 — About

A data analyst who lets the numbers do the talking.

I'm Aditya — a data analyst working at Cityfurnish, where I build the dashboards, models and automation that keep a 10K+ asset operation running.

My toolkit: SQL for the heavy queries, Power BI & Looker Studio for the storytelling, Python (Pandas & web scraping) for the messy work, and Excel + DAX for everything in between.

I'm currently pursuing my M.Sc in Computer Science & Data Analytics at IIT Patna, alongside hands-on work that's reduced customer defaults by 17%, increased peak transactions by 10%, and shipped 20+ BI dashboards.

02 — Skills

My stack — what I reach for daily.

SQL & MySQL

Complex joins · CTEs · Window functions

Power BI

DAX · Power Query · Modeling

Advanced Excel

Formulas · Pivots · Excel automation

Python

Pandas · BeautifulSoup · Selenium

Tableau

LOD · Calculations · Stories

Looker Studio

BI dashboards · Live data

ETL & Modeling

Power Query (M) · Validation · Cleaning

Statistical Analysis

EDA · Trend & variance · Forecasting

Learning next

● Q3 2026 · Data Engineering

In progress

dbt

Models · Tests · Lineage · Analytics engineering

In progress

Apache Airflow

DAGs · Scheduling · Orchestration

In progress

Snowflake

Cloud DW · Warehousing · Performance tuning

In progress

Docker

Containers · Compose · Reproducible envs

03 — Work

Selected projects with code on GitHub.

Analysis · SQL

Retail Sales Analysis

Analysed 10K+ transactions in SQL — identifying top revenue-generating categories, peak sales months, and category concentration.

Where I'm working now.

Aug 2025 — Present

MIS Executive

Cityfurnish · Gurugram, India

Extracted and analysed 10K+ asset warehouse & operational datasets using SQL, Excel, and Python — generating insights to improve asset utilisation and operational efficiency.
Designed and automated 20+ BI dashboards in Power BI and Looker Studio — real-time monitoring of inventory utilisation, refurbishment cycles, pricing and warehouse KPIs.
Cleaned and transformed 100K+ records using Power Query and Pandas to ensure high-quality data for analytics.
Time-series analysis on Razorpay transactions identified peak patterns and gateway issues — +10% peak-hour transactions, +5% payment success rate.
Built a Python web-scraping tool for competitor price benchmarking across 100+ SKUs daily, supporting revenue optimisation.
Pricing, yield and demand elasticity analysis — kept assets above the 6% yield threshold while identifying optimal price points to maximise order volume.
Designed an automated order-to-invoice reconciliation framework — validating mapping across website orders, recurring billing and warehouse deductions.
Customer risk & behavioural analytics identified high-risk segments through geographic and behavioural patterns — reduced customer defaults by 17%.