Exploratory Data Analysis (EDA)
Also written as Exploratory Data Analysis, Data Exploration, Data Profiling
The first look at a new dataset before any modelling: what each column contains, missing values, outliers, distributions and relationships, mostly through summary tables and charts in pandas or notebooks. It decides what cleaning and features the model will need.
Think of it like
Walking round a house before quoting for the renovation: you look in every room before deciding what to fix.
Junior or senior?
Every data science resume lists it.
Senior sounds like
Can name something EDA revealed that changed the plan, such as leaked data, a broken column or a biased sample.
Ask them
“What's something you found during EDA that changed your plan for the model?”
Reading Exploratory Data Analysis (EDA) on a resume
- Table-stakes
- Most people in this field list Exploratory Data Analysis (EDA), so its presence tells you little, and opening a screen with it can make the call sound junior. Ask what they built with it instead.
Sourcing for Exploratory Data Analysis (EDA)
Every way it's written
("Exploratory Data Analysis" OR "Data Exploration" OR "Data Profiling")Paste into LinkedIn Recruiter, Naukri or your ATS. Combine with a job title and location.
Job titles to search alongside it
Machine Learning Engineer · ML Engineer · AI Engineer · Applied Scientist · MLOps Engineer · Data Scientist
Where this talent works in India — AI & Machine Learning
Target companies with models in production and their own training or inference spend — hyperscaler AI teams, consumer platforms with ranking systems, and funded model startups. Analytics-only shops produce the job title without the delivery.
For example: Google (Research and DeepMind India), Microsoft (including Microsoft Research India), NVIDIA, Adobe, Amazon, Salesforce, Uber, Sarvam AI.