Viva Soft Skills
Self-intro, "why bKash", CV deep-dive prep, questions to ask the panel.
Start here
Everything technical you've prepared can be undone by a shaky self-introduction or a generic "I like fintech" answer — this module is the delivery layer on top of modules 1-8, and it's graded just as seriously.
A viva board checks not just whether you know the answer, but whether you can communicate it clearly under mild pressure, in a way that builds trust:
- A self-introduction that's timed and rehearsed, not improvised for the first time in the room.
- Reasons for wanting this specific role that are concrete, not generic.
- Comfort discussing anything on your CV in depth — everything on it is fair game.
- Genuine curiosity about the team, shown through the questions you ask back.
None of this is performing confidence you don't feel — it's removing avoidable friction (forgetting your own pitch, going blank on your own CV) so the other eight modules' prep actually comes through when it matters.
Core threads
- 60-second self-introduction: background → most relevant project/thesis (one sentence hook) → why you're excited about this specific role. Practice it timed — 60 seconds is shorter than it feels.
- "Why bKash / why this role": connect *your* specific skills to bKash's actual ML problems (fraud, credit scoring, /KYC, chatbots) — generic "I love fintech" answers are forgettable.
- "What ML problems does an MFS company face?": fraud/anomaly detection, credit scoring for the unbanked, churn prediction, personalized offers/recommendation, for KYC documents, chatbot/IVR intent classification, Bangla NLP for support tickets.
- CV deep-dive: expect detailed questions on *anything* listed — if you wrote "implemented a ," be ready to explain every architecture choice you made and why.
- Questions to ask the panel: prepare 2 genuine ones — e.g. "what does the first 90 days on the ML team look like?", "what's the biggest technical challenge the team is solving this year?" Avoid asking about salary/benefits in a technical viva round.
Viva angle
Confidence reads as much through pacing and eye contact as content — rehearsing out loud (not just reading silently) is the single highest-leverage prep action here.
Visual reference
60-second self-intro shape
Cheatsheet
60-second self-intro shape
| ~20s | ~20s | ~20s |
|---|---|---|
| Background | One concrete project/thesis hook | Why this role, specifically |
- ▸Everything on your CV is fair game — only list what you can defend in depth.
- ▸Prepare 2 genuine questions for the panel; skip salary/benefits in a technical round.
- ▸Rehearse out loud, timed — recognizing an answer while reading is not the same as saying it fluently.
Further study
Question bank
11 questionsHow should you structure a 60-second self-introduction for a technical viva?
How do you give a strong, specific answer to "why bKash / why this role" instead of a generic one?
List the major ML problem categories a mobile financial services (MFS) company faces.
Why is it risky to list a tool/technique on your CV that you can't explain in depth?
What kind of questions should you prepare to ask the panel at the end of a technical viva?
Why does rehearsing answers out loud matter more than just reading notes silently?
How do you answer "What's your biggest weakness?" honestly without sabotaging yourself?
How should you structure an answer to a behavioral question like "tell me about a disagreement with a teammate"?
Why is explaining a technical ML concept to a non-technical stakeholder a skill panels actually test for in a research-facing role, and how do you do it well?
How should you respond gracefully when you genuinely don't know the answer to a question in the viva?
How do you answer "Where do you see yourself in five years?" in a way that actually helps your candidacy?