Tech & product grad assessments in Southeast Asia
Tech companies in Southeast Asia — Grab, Shopee, GoTo, Stripe, Google, Meta — test differently from banks. The aptitude component is shorter, but it sits alongside coding challenges or product sense questions that are unique to tech hiring.
- Tech assessment prep depends heavily on role: SWE, PM, data and ops are different.
- Aptitude tests are usually a filter; technical screens decide much of the outcome.
- Product/data candidates should practise metrics, funnels and trade-offs.
- SWE candidates should not ignore numerical/logical screens just because coding matters.
If your invite includes aptitude plus a technical task, practise them separately. See practice
What to focus on first
| Focus area | Why it matters | Best drill |
|---|---|---|
| SWE | Coding screens dominate, but aptitude can still filter. | Arrays, strings, trees plus timed logical drills. |
| Product | PM tasks test metrics and user trade-offs. | DAU, retention, activation and conversion scenarios. |
| Data analyst | SQL and chart interpretation often sit together. | Funnel maths plus data interpretation drills. |
| Operations | Judgement and numerical reasoning show up frequently. | SJT scenarios plus table-reading speed. |
Common traps
- Assuming tech means no aptitude. Many graduate routes still use SHL, AON or game-based filters.
- Practising LeetCode only. PM and data tasks often test business interpretation.
- Missing metric definitions. DAU, MAU, retention and conversion are not interchangeable.
How to practise from here
Build a two-track plan: one short aptitude drill and one role-specific technical drill each day. Keep the aptitude practice timed so it does not drift into relaxed study.
The typical tech pipeline
- Online application + resume screen.
- Aptitude test — usually SHL or AON, sometimes Pymetrics. 20–40 minutes.
- Technical screen — coding (SWE), product case (PM), SQL/analytics (DA).
- On-site / virtual interviews — 3–5 rounds, mix of technical and behavioural.
What makes tech aptitude tests different
Tech companies tend to use shorter batteries (numerical + logical, skip verbal) and weight the results less heavily than banks do. The test is a filter, not a ranking tool. Pass the cutoff and the coding screen becomes what matters.
Product metric questions
PM and DA roles increasingly include a “product metric interpretation” section. You see a dashboard (DAU, retention, conversion) and answer questions about what changed and why.
Users are still active monthly but visiting less frequently. Possible causes: a feature change reduced daily engagement, a push notification was disabled, or seasonality (e.g., post-holiday drop). The answer is about engagement frequency, not user churn.
1,800 / 10,000 = 18%. The activation bottleneck (60% activation rate) is the biggest drop — fixing it has more leverage than improving purchase from activated users (1,800 / 6,000 = 30%, which is already reasonable).
How to prepare
- Aptitude: 1 week of focused numerical + logical practice. Tech tests are easier than bank tests — but they still filter.
- Product metrics: Read dashboards daily. Practice interpreting changes in DAU, retention curves, and conversion funnels.
- Coding (SWE): LeetCode medium, focus on arrays, strings, trees, and dynamic programming.
How to choose your route
The invite wording decides the prep. If it says coding, prioritise algorithms and data structures. If it says product case, practise metric interpretation and trade-offs. If it says SHL, AON or Pymetrics, use the relevant psychometric test route first. For PM and data roles, combine data interpretation with a short verbal explanation of what the metric change means.
A good rule is to split your prep by score weight and uncertainty. Coding screens usually carry the most weight for SWE roles, so do them daily. Product and data candidates should spend more time on business reasoning because a small metric mistake can make the whole written answer look weak. Aptitude should sit underneath both tracks: short timed sets that keep the filter from becoming the reason you never reach interview.
Source notes
forge checks assessment-format guidance against official provider pages from SHL, Harver/pymetrics, and HireVue. Company-specific technical screens vary by role and season.
Prep for tech assessments on forge
Numerical, logical, and Pymetrics practice — tuned for the shorter, faster tests tech companies use.
Start preparingFrequently asked questions
Do tech graduate roles still use aptitude tests?+
Yes. Many tech, product and data graduate routes still use numerical, logical, game-based or SJT-style screens before technical interviews.
How should product candidates prepare?+
Practise funnel metrics, retention, activation, conversion and short business interpretation alongside any numerical or logical reasoning test.
How should SWE candidates split prep?+
Keep coding practice primary, but do short timed logical or numerical drills if the invite includes an aptitude screen.
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