Spokeo

Mid-sized

Spokeo is a people search engine that aggregates publicly available data to help users find and verify information about individuals, including contact details, social media profiles, and background information. It is known for its consumer-facing lookup services used for reconnecting with people and identity verification.

9 interview notes · updated Jul 2026

Spokeo·Data Scientist·Technical Phone Screen

Jul 2026

Rapid-fire ML fundamentals session with the CIO at Spokeo for a Data Scientist role. The whole thing felt like a verbal exam, back-to-back questions with barely any room to breathe between them.

Can you explain the bias-variance trade-off and what it means in practice?
Define overfitting and underfitting, and walk through some techniques to prevent each.
What is regularization, and what's the practical difference between L1 and L2?
Describe k-fold cross-validation and explain why it's a better evaluation strategy than a simple train-test split.
What are the key assumptions that need to hold for linear regression to be valid?

“I actually felt okay here.”

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Spokeo·Data Scientist·Recruiter / HR Screen

Jul 2026

Phone screen with an HR rep at Spokeo for a data scientist role. Pretty much all model evaluation vocabulary, nothing hands-on, but they pushed you to actually justify your answers in a business context which I was not fully ready for.

Define precision, recall, specificity, and F1-score and explain what each one actually measures.
What does a p-value represent?
In a fraud detection context, which matters more: false positive rate or false negative rate? Make an argument either way.

“I knew the definitions but stumbled when they asked me to contrast specificity and recall on the spot.”

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Spokeo·Data Scientist·Online Assessment (OA)

Jun 2026

Took the HackerRank screening for a Data Scientist role at Spokeo. It was a timed stats quiz, no coding, just pure statistics fundamentals. Pretty straightforward if you've kept your theory sharp, but the time pressure made me second-guess myself on a couple of the interpretation questions.

What are the expectation and variance of a Poisson distribution with parameter λ?
Given a known population standard deviation σ and sample size n, write out the 95% confidence interval for the population mean.
In what situations should you use a two-sample t-test rather than a z-test?
State the Central Limit Theorem and give one practical implication of it.
How would you interpret a p-value of 0.03 in a hypothesis testing context?

“Both are λ.”

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Spokeo·Data Scientist·Hiring Manager Screen

Jun 2026

Hiring manager screen for a data scientist role at Spokeo, focused entirely on experiment design for a TV advertising campaign. One meaty question that took up most of the time.

Walk through how you'd design a controlled TV advertising experiment to drive website sign-ups. Cover the hypothesis, how you'd randomize, which KPIs you'd track, sample size, how long you'd run it, and what success looks like.

“This one went deeper than I expected for a hiring manager conversation.”

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Spokeo·Data Scientist·Hiring Manager Screen

May 2026

Behavioral screen for a Data Scientist role at Spokeo. Pretty standard HR chat, nothing too surprising, mostly the usual background and motivation questions you'd expect before any technical rounds.

Give a two-minute self-introduction and walk me through your resume.
Why do you want to join Spokeo?
Why did you leave industry to go back for a graduate degree?
Describe the most challenging part of a past project and how you handled it.
How do you stay current with how fast the technology landscape is changing?

“Practiced this a dozen times and still ran a bit long.”

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Spokeo·Data Scientist·Online Assessment (OA)

May 2026

Spokeo data scientist interview had a HackerRank notebook task using the Titanic dataset. Pretty classic EDA stuff but the open-ended nature of it meant you had to decide what mattered and actually explain your thinking, not just produce output.

Given a Titanic passenger dataset, perform an exploratory data analysis: compute survival rate broken down by sex, average age per passenger class, and the correlation between age and survival. Include labeled visualizations and a brief discussion of what the data shows.

“The EDA itself wasn't hard but I spent too long on the correlation piece.”

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Spokeo·Data Scientist·Hiring Manager Screen

May 2026

Had a hiring manager technical discussion at Spokeo for a data scientist role, pretty deep dive into system design territory. The whole conversation centered on building a recommendation system from scratch, which I wasn't expecting to go as broad as it did.

Walk through how you'd design a full recommendation system for Spokeo, from data collection all the way through feature engineering, model selection, evaluation, real-time serving, and an A/B testing plan.

“This was basically the entire interview crammed into one question.”

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Spokeo·Data Scientist·Technical Phone Screen

May 2026

Had a business analytics conversation at Spokeo for a Data Scientist role that leaned heavily into revenue modeling. One meaty CLV question basically carried the whole session.

How would you calculate Customer Lifetime Value for Spokeo? Walk through the data you'd need, the assumptions you'd make, which model you'd use, and how you'd validate it.

“This one took longer than I expected to get my footing on.”

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Spokeo·Data Scientist·Onsite - Coding / Algorithms

Apr 2026

Onsite at Spokeo for a Data Scientist role where the hiring manager and VP sat in and ran me through a logic/puzzle gauntlet. Six AMC-8 style problems including the river-crossing classic. Not what I expected walking in.

Solve a set of six math and logic puzzles, including the farmer-fox-chicken-grain river-crossing problem, and explain the algorithm and why it works.

“The river-crossing one I actually knew, but they wanted a formal proof of correctness, not just the answer.”

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