Meta·Data Scientist·Technical Phone Screen
May 2026
Product analytics case for Meta DS, focused entirely on a group calling feature launch. Four connected questions that built on each other, which I wasn't expecting. The network effects angle at the end is where things got uncomfortable.
- What survey questions would you design to uncover user needs around a group calling feature, for both current and potential users?
- Without direct access to competitor data, how would you benchmark how widely group calls are being adopted on competing platforms?
- Design an experiment to measure the causal impact of launching group calls. Define your treatment and control groups, your primary metric, and any guardrail metrics. Also explain whether total call volume is the right primary metric.
- Group calling has strong network effects, which makes standard A/B testing prone to spillover. If a cluster-randomized experiment isn't feasible due to engineering constraints, what alternative approaches could you use to measure causal impact?
“I started with feature importance ratings and willingness to pay, which felt solid.” The rest of the author's notes on Data Scientist interview at Meta, Technical Phone Screen round, covers how they worked through the question, what the panel pushed back on, and what they would do differently.
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