In-depth guides for top tech company interviews. Each guide covers the interview process, question types, preparation tips, and includes real practice questions.
9,429 guides across 7,316 companies · page 47 of 158
Amazon Lab126 Software Engineer interview guide: reported rounds, questions and how candidates describe the process.
Allegis Group Software Engineer interview guide: six reported rounds, coding questions, REST and OOP prep, behavioral stories and a 7-day plan.
AIR Software Engineer interview guide: recruiter screen, technical dives and team fit, with answers on microservices, API design and a 7-day plan.
Adani Digital Labs Software Engineer interview guide: the reported rounds, OOP, merge sort, SQL vs NoSQL and two-sum prep, plus a 7-day plan.
ADM Associates Software Engineer interview guide: R, Excel, regression, HVAC basics, behavioral questions and a 7-day prep plan.
AbbVie Software Engineer interview guide: reported rounds, questions and how candidates describe the process.
Bilfinger Software Engineer interview guide: reported rounds, questions and how candidates describe the process.
Motive Software Engineer interview guide: 6 reported rounds, Minesweeper and BST coding, fleet-tracking system design, Topgrading prep, and a 7-day plan.
Code reading practice for Walmart Global Tech software engineer prep: work out what unfamiliar code does before judging it.
A prep plan for Verisign software engineer candidates: answer first, read the solution second, repeat the misses later.
Timed coding practice for Walmart software engineer candidates: full attempts under a clock, then scored against a rubric.
Timed coding practice for Square software engineer candidates: full attempts under a clock, then scored against a rubric.
Sonos software engineer prep on operations: decide what you would need to see to know a release is going wrong.
API design practice for KAYAK software engineer candidates: compatibility, versioning, and changes you cannot take back.
Take-home style practice for Pigment software engineer candidates: a small service, a fixed budget, a written tradeoff.
Debugging practice for Airtable software engineer candidates: reproduce it, narrow it, then change one thing per run.
Caching practice for Cloudera software engineer prep: settle the staleness budget before choosing an invalidation strategy.
Take-home style practice for RSquareSoft Technologies software engineer candidates: a small service, a fixed budget, a written tradeoff.
Isar Systems and Technologies Private software engineer prep on partial failure: a timed-out request has an unknown outcome, not a failed one.
Software engineer interview prep for Nex: original coding, system design and debugging practice, each with a worked solution.
Software engineer interview prep for Femtosoft Technologies: original coding, system design and debugging practice, each with a worked solution.
A prep plan for SCA Health software engineer candidates: answer first, read the solution second, repeat the misses later.
API design practice for Safe-Guard Products International software engineer candidates: compatibility, versioning, and changes you cannot take back.
Timed coding practice for Service Stream software engineer candidates: full attempts under a clock, then scored against a rubric.
Software engineer interview prep for OCBC Indonesia: original coding, system design and debugging practice, each with a worked solution.
API design practice for BCA software engineer candidates: compatibility, versioning, and changes you cannot take back.
Software engineer prep for TekniPlex: design exercises weighted toward the constraints of supply chain and logistics work.
A two-week prep plan for Wolverine Trading data scientist candidates: write your answer before reading the solution, revisit misses three days later.
SQL practice for Zendesk data scientist candidates: window functions, funnel and retention queries, joins that quietly drop rows.
Data scientist interview prep for Zynga: original practice on experiment design, SQL and metric reasoning, with worked solutions.
Practice explaining analysis before a Verisk data scientist interview: the recommendation, the uncertainty, the follow-ups.
the LEGO Group data scientist prep on data pitfalls: selection bias, target leakage, and checking an outlier's provenance before you drop it.
University of Oxford Data Scientist interview guide: reported rounds, practice questions with worked solutions and a 7-day prep plan.
Case practice for Tulk data scientist candidates: scope a vague prompt into a measurable question before you analyze it.
Causal inference drills for Toyota data scientist prep: diff-in-diff, matching, instruments, and the limits of observed data.
TomTom data scientist prep: probability, sampling distributions, and stating the assumption behind every test you run.
A two-week prep plan for Smartsheet data scientist candidates: write your answer before reading the solution, revisit misses three days later.
SentiLink data scientist prep: probability, sampling distributions, and stating the assumption behind every test you run.
Data scientist prep for Schonfeld: practice defining a quantitative trading metric, picking its guardrails and defending the tradeoff.
Case practice for Radiance Technologies data scientist candidates: scope a vague prompt into a measurable question before you analyze it.
Data scientist prep for Optum Financial candidates: drill A/B design, power and minimum detectable effect on original exercises.
Timed data scientist practice for Pra Health Sciences: short SQL and probability sets run end to end, then scored against a rubric.
Neuron7 Data Scientist interview guide: reported rounds, practice questions with worked solutions and a 7-day prep plan.
Data scientist prep for Moody's: practice defining a B2B software and infrastructure metric, picking its guardrails and defending the tradeoff.
A two-week prep plan for Nyla Technology Solutions data scientist candidates: write your answer before reading the solution, revisit misses three days later.
SQL practice for NewsBreak data scientist candidates: window functions, funnel and retention queries, joins that quietly drop rows.
Northern Trust data scientist prep on data pitfalls: selection bias, target leakage, and checking an outlier's provenance before you drop it.
Case practice for NASA data scientist candidates: scope a vague prompt into a measurable question before you analyze it.
Diagnose a metric move for Nielsen data scientist prep: split by segment, rule out a logging change, separate mix shift from behaviour.
MTSI data scientist prep on data pitfalls: selection bias, target leakage, and checking an outlier's provenance before you drop it.
LSEG (London Stock Exchange Group) data scientist prep: probability, sampling distributions, and stating the assumption behind every test you run.
Case practice for Meta Power Solutions data scientist candidates: scope a vague prompt into a measurable question before you analyze it.
Practice explaining analysis before a ING data scientist interview: the recommendation, the uncertainty, the follow-ups.
SQL practice for KDA Consulting data scientist candidates: window functions, funnel and retention queries, joins that quietly drop rows.
A two-week prep plan for John Deere data scientist candidates: write your answer before reading the solution, revisit misses three days later.
Causal inference drills for Hastings Direct data scientist prep: diff-in-diff, matching, instruments, and the limits of observed data.
Practice explaining analysis before a GSK data scientist interview: the recommendation, the uncertainty, the follow-ups.
Data scientist prep for Freshworks: practice defining a B2B software and infrastructure metric, picking its guardrails and defending the tradeoff.
Data scientist prep for Factual candidates: drill A/B design, power and minimum detectable effect on original exercises.
Experian data scientist prep on data pitfalls: selection bias, target leakage, and checking an outlier's provenance before you drop it.