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By Mockly English · Last updated:
How a Senior Data Scientist Prepared for Google and Revolut Cases in English
He had already sat Google. Revolut’s product case was next — in English.
At a glance
| Role | Senior data scientist (cybersecurity background; targeting lead) |
|---|---|
| Region | From Russia; Singapore for 4 years |
| Starting Point | Hard to explain technical work and cases in English |
| Target | Big Tech; Google already interviewed; Revolut case next |
| Outcome | MECE case structure + leadership vocabulary |
Timeline
Senior DS
Focus
Google loop (past)
Outcome
Revolut case ahead
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“I can see the metric drop. I need the English to walk a VP through why — without drowning them in method.”
The Problem
He was a senior data scientist aiming at a manager or team-lead seat. He had already interviewed at Google and had a Revolut case on the path. Cybersecurity work was technically deep. In English, project explanations and product cases stalled: a metric drop, a new market, an A/B test — he could solve them and still not sound like a mini-CEO inside the business. Leadership vocabulary was part of the brief, not a separate course.
Before and After
Before coaching
- Struggled to explain technical concepts in English
- Cases lost the business recommendation
- Google loop already happened without enough case English
- Lead-level vocabulary was missing
After coaching
- MECE case frames for metric and launch problems
- Statistics used as support, not the whole answer
- Project stories with a result a hiring manager can repeat
- Language for leading a slice of the product
What We Practised
Hours looked like Revolut and Big Tech cases: a metric drop, a moderation system, a launch in a new country. English feedback landed on the same case — structure, stats, and the recommendation.
- Product cases: regional user drop, content moderation, A/B tests
- MECE framing plus enough statistics to defend the call
- Leadership vocabulary for a senior-to-lead jump
- Explaining DS projects without drowning in method
Useful references along the way: Pronouncing numbers and metrics, STAR interview framework.
Starting Point
Four years in Singapore, originally from Russia. Tennis and travel outside work. Interview formats he asked for: product cases first (users drop in a region; content moderation; Vietnam launch / A/B test), behavioral later. Revolut specifically: run a mini-startup inside the company, with statistics in the argument.
The interview process
| Already interviewed (notes do not record an offer) | |
| Revolut | Product case / mini-CEO format ahead |
| Coaching focus | Cases first; behavioral later |
The Result
He had already sat Google. Coaching was for the next cases — especially Revolut — and for sounding like someone who could own a problem in English, not only compute it. Notes do not claim a Google or Revolut offer.
What He Would Do Differently
- Practise product cases before the first Big Tech loop, not after
- End every case with a recommendation in one sentence
- Prepare lead-level language even if the CV still says IC
- Use statistics as evidence, not as the plot
Why This Matters for Data Scientists Interviewing at Google or Revolut
DS loops at product companies are cases, not Kaggle recitals. Google and Revolut both reward a clear decision in English. Senior ICs who skip that practice sound more junior than their models.
Preparing for a similar path? Read How an Israeli Account Manager Prepped for Google in English.
Frequently Asked Questions
How do you prepare for a Revolut data science case in English?
Practise mini-CEO cases: structure the problem, use stats to support one decision, and say the recommendation out loud.
I already interviewed at Google. Is more English coaching useful?
If another product case is coming, yes. A past loop does not bank spoken structure for the next company.
What is MECE in an interview answer?
A way to split the problem into parts that do not overlap. It only helps if you can say the split clearly.
Should data scientists practise leadership language?
If you want a lead seat, yes. Interviewers listen for ownership, not only for p-values.
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Mockly’s approach is genuinely personalized — they use a variety of methods tailored to your specific needs. With their help, I improved my spoken English and prepared thoroughly for behavioral interview questions across different companies. This not only helped me refine my stories grammatically but also ensured I was using the right examples to answer specific questions effectively.
Mockly was a huge help in preparing for my interviews. We worked on both technical and behavioral questions, and I received great advice on how to approach them and what to focus on. I feel significantly more confident as a result. They also helped me with my CV and cover letter — showing me how to structure them properly and highlight my strengths. I appreciate that they always ask how you’d like to structure your sessions and adjust to your goals. It keeps you on track and makes the whole process far more effective.
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