Tencent·Data Scientist·Technical Phone Screen
Jul 2026
Tencent DS interview with a single massive multi-part question about offline email deliverability optimization. The whole thing was one long problem broken into seven sub-parts, which felt more like a take-home disguised as a live session. Brutal scope.
- You need to finalize the design of an in-game transactional email to minimize the chance it gets classified as Promotional or Spam by mailbox providers, but you can't run any live A/B tests or collect post-send feedback. You have 12 months of historical email data with send metadata, domain info, anchor text types, sender reputation metrics, and folder labels from seed inboxing tests. Your design variables are number of links, which domains to include, anchor text style, subject tokens, and whether to use a hero image. Formulate an offline risk-minimization problem: write the objective, constraints, and any robustness term you'd include such as worst-case over providers or conformal upper bounds.
- What features would you engineer and what modeling approach would you use to estimate the risk of a given email design being classified as Promotional or Spam? How do you prevent data leakage, especially around template IDs and time-based splits, and how do you calibrate the predicted probabilities?
- The new email design may look quite different from anything in the historical training data. How would you handle covariate shift between past templates and the proposed new design when making risk predictions?
- How would you search over the discrete design space to find the lowest-risk email configuration? Describe your optimization strategy.
- Without any new user feedback, how would you validate that the chosen email design is actually lower risk? Walk through your offline evaluation approach.
- Some providers have scarce or noisy historical labels. What fallback would you use, and how would you quantify the added uncertainty in your final risk estimate?
- Give a concrete decision rule for selecting the final email design. What threshold would you set for the worst-case provider risk upper bound, and why?
“This sub-part alone could be a full interview.”