How do you treat missing values without inventing fake certainty?
PICTURE THIS: DOM IS A TREE
html
headbody
navmainfooter
Simple meaning
Drop when rare and random
WHY — Cleaning instead of guessing?
Why interviewers care about Cleaning:
This is a process
question about Cleaning.
Panels listen for order,
trade-offs, and what you would actually do on a Data Science project - not buzzwords.
Stay structured
Name the idea, why it exists, then one short example.
Close cleanly
End with when you use it and one common pitfall.
STEPS — What happens step by step?
Before you speak the answer, walk the interviewer through these steps:
- 1Define it
Drop when rare and random
- 2impute with care and
flag missingness.
- 3Missingness itself can be
a signal.
- 4Give an example
I document the choice.
- 5Common mistake
What juniors usually get wrong.
- 6Close
When you pick this over the alternative.
EXAMPLE — See it in action
Here's a short line you can speak, broken into clear beats:
Say this line
“Missingness itself can be a signal.”
Break into beats
Missingnessitselfcanbeasignal
Speaking order
2987408337471632900
Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.
Key takeaway
Drop when rare and random impute with care and flag missingness.