24/7.ai Data Science Interview Questions and Answers (2026 Guide)

Quick answer: The most detailed, individually attributable interview account we found for a [24]7.ai Data Scientist role, in its Data Sciences Group (DSG), describes 4 telephonic rounds: basic maths, puzzles and Matlab with a DSG manager, a resume and final-year-project discussion, a technical round on probability, statistics, machine learning algorithms and speech processing, and an HR round. A separately reported Business Analyst track runs HR screening, a job-and-responsibilities technical round, and a case-study round built around business puzzles like diagnosing a sales drop. Company-wide, Glassdoor's aggregate rates the interview experience 2.84 out of 5 for difficulty with 62.1% positive feedback across 133 submitted interviews, and specifically flags Data Science roles as among the hardest at the company.

About [24]7.ai

[24]7.ai, styled with brackets and also written 24/7.ai, is a conversational-AI and customer-experience company founded in April 2000 in California as 24/7 Customer, Inc. It dropped "Customer" from its name in 2012, the same year Microsoft became an equity investor and transferred roughly 400 employees from its Tellme Networks voice-recognition unit, then added ".ai" in October 2017 to reflect its AI focus. (Wikipedia) The company's own site lists more than 10,500 employees globally, headquartered in Campbell, California, with delivery centers across the United States, India, the Philippines, Colombia, Guatemala, South Africa and Egypt. (247.ai, About Us) Its India delivery centers are reported in Bangalore, Hyderabad and Shillong, and its flagship [24]7 Engagement Cloud platform is built on conversational AI and voice technology, a lineage that traces partly to the Tellme acquisition and surfaces directly in the speech-processing question theme reported below.

[24]7.ai's Interview Process

• Data Scientist, Data Sciences Group (DSG) track: one detailed candidate account describes 4 telephonic rounds. Round 1, with a DSG manager, covers basic maths, puzzles, basic data-structure code and questions in Matlab. Round 2 focuses on your resume and final-year project: its real-world application, the algorithms used, and how clearly you can explain them. Round 3 is a technical round on probability, statistics, machine learning algorithms, speech processing, and some Java. Round 4 is HR, reported as straightforward once the technical rounds are cleared. (Glassdoor)

• Business Analyst track: reported as an HR screening round assessing communication and role fit, followed by two technical rounds, one covering the job and BA responsibilities directly, the other a case-study round built around business puzzles and guesstimates, for example analysing a drop in sales or evaluating a new product launch, then a managerial round and a final HR discussion on compensation and offer details. (Glassdoor)

• Company-wide aggregate: Glassdoor's summary across all [24]7.ai roles, from 133 submitted interviews, rates the experience 62.1% positive with a difficulty of 2.84 out of 5 and an average 15 days to hire. The same summary specifically names Data Science and Advisor roles as the hardest interviews at the company, and Major Account Executive and Analyst roles as the easiest. (Glassdoor)

What Candidates Report

Across the DSG and Business Analyst accounts above, recurring themes are probability and statistics fundamentals, core machine learning algorithms, a dedicated resume-and-project deep dive, and business case-study or guesstimate-style puzzles rather than pure SQL drills. Speech processing shows up as a specific DSG topic, consistent with the company's voice and conversational-AI product line. Separately, three fully readable candidate write-ups on GeeksforGeeks, under a "[24]7 Innovation Labs" heading, describe a heavily DSA- and system-design-focused process (stack and linked-list problems, an LRU cache implementation, BST traversal, designing a chess game or a meeting scheduler) for what reads as general software-engineering hiring, not a data-analyst or data-scientist role. We are naming these accounts and flagging them as engineering-specific rather than folding their questions into a data-analytics list, since doing that silently is exactly the mistake this series exists to avoid.

What We Could Not Verify

Both Glassdoor interview pages cited above returned a direct-fetch access error for us, so the process detail comes from search-indexed summaries of those pages rather than pages we read in full ourselves. AmbitionBox did not return usable content for this company (a direct load attempt timed out), and Naukri Code360's [24]7.ai interview bundle also blocked direct access. We found no DataLemur question set for this company, unlike several peers in this series. The DSG account's mention of Matlab and Java, with no date attached, means we cannot confirm it reflects [24]7.ai's current interview format rather than an older one, so treat the specific tools named there as illustrative of one candidate's experience, not a guaranteed current syllabus.

How to Prepare

• Revise probability, statistics and core ML algorithms, the one technical theme consistently confirmed for the DSG Data Scientist track.

• Prepare one project you can explain end to end: its real-world application and the algorithms behind it, since resume-and-project discussion is its own dedicated round here.

• Practise business case-study and guesstimate questions, such as diagnosing a sales drop or sizing a new product opportunity, for the Business Analyst track.

• Keep basic coding and data-structure fundamentals sharp even for analytics-adjacent roles, given how DSA-heavy the company's broader engineering hiring reads across independent accounts.