01 — SKILLS

More
than
tools.

I have built my skills by working on different kinds of problems — from analysing scientific data to building financial models, dashboards and business presentations.

The tool matters. Knowing what to do with it matters more.
02 — MY TOOLKIT

Different questions
need different tools.

My background brings together Data Science, Finance and Business Intelligence. I use these areas together rather than treating them as separate skill sets.

Sometimes that means writing Python to understand a dataset. Sometimes it means building a financial model in Excel, creating a Power BI dashboard, exploring data in Tableau or Looker, or putting the findings into a clear presentation for a business audience.

03 — ANALYTICS & DATA

Analytics & Data

I use data to understand what is happening, identify patterns, test assumptions and build evidence for a decision.

Python Pandas NumPy Scikit-learn Machine Learning NLP Time Series Statistical Analysis Data Cleaning Data Transformation Orange Data Mining
Where I have used it IIRS–ISRO research, academic projects and analytical work
04 — BUSINESS INTELLIGENCE

Business Intelligence

I use BI tools to turn analysis into something people can quickly understand, explore and use for decision-making.

Power BI Tableau Looker Excel Dashboards Data Visualization Reporting
Where I have used it Dow customer analytics, business reporting and academic projects
05 — FINANCE & QUANTITATIVE ANALYSIS

Finance & Quantitative Analysis

Finance has taught me to look beyond the numbers and think about value, risk, returns and the trade-offs behind a decision.

Financial Modelling Corporate Finance Investment Analysis Financial Statement Analysis Valuation Portfolio Analysis Risk Analysis Quantitative Finance
Where I have used it Project Prarambh, Sectoral Analysis and finance coursework
06 — PROGRAMMING & DATA WORKFLOWS

Programming & Data Workflows

I use programming to bring structure to data — from preparing raw information to creating repeatable workflows for analysis.

Python SQL ETL Data Pipelines
Where I have used it Data Science coursework, research and analytical workflows
07 — BUSINESS & PROBLEM SOLVING

Business & Problem Solving

This is where the technical and financial sides come together. I focus on understanding the problem, structuring the analysis and communicating the result clearly.

Business Analysis Market Analysis Process Improvement Process Mapping Customer Analytics Forecasting Strategic Analysis Stakeholder Management Research Consulting Presentations Storytelling
Where I have used it Dow, Nobelza, Project Prarambh and academic business projects
08 — HOW I WORK

Understand first.
Then analyse.

I have found that having the right tool is only one part of good analysis. The more important part is understanding the question and knowing how the result will be used.

01 Understand

What is the problem, and why does it matter?

02 Structure

Break the problem into questions that can actually be answered.

03 Analyse

Choose the data, methods and tools that fit the question.

04 Communicate

Turn the findings into clear analysis, dashboards or consulting-style presentations.

05 Act

Connect the analysis to a practical next step.

LET’S CONNECT

The tool changes.
The approach stays.

I am constantly learning new tools, but I care just as much about how I use them — whether that means building a model, creating a Power BI dashboard, exploring data in Tableau or Looker, analysing a dataset in Python, or presenting an idea clearly to a business audience.

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