Technical assessments verify job-specific skills and knowledge. From coding challenges to engineering principles, these tests ensure candidates have the technical foundation for the role.
Technical assessments verify role-specific skills and knowledge. For technology roles, this typically means coding challenges (Codility, HackerRank, LeetCode-style). For engineering roles, it may include mechanical reasoning, CAD skills, or domain-specific knowledge. For finance roles, it may include financial modelling or Excel proficiency tests.
Understanding the different formats helps you prepare more efficiently.
Write code to solve algorithmic problems. Assessed on correctness, efficiency, and code quality. Platforms: Codility, HackerRank, CoderPad.
Multiple-choice questions testing domain knowledge (e.g., networking, database concepts, financial instruments).
Apply technical knowledge to a realistic business scenario. Common in consulting and finance.
Demonstrate proficiency in specific tools (Excel, SQL, Python, CAD). Often includes practical tasks.
Proven techniques to maximise your Technical score.
Different coding platforms (Codility, HackerRank, CoderPad) have different interfaces and constraints. Practice on the specific platform you will use.
Most coding assessments test fundamental data structures and algorithms: arrays, strings, hash maps, trees, sorting, and searching. Master these before advanced topics.
In live coding interviews, explain your approach before coding. Interviewers value clear thinking as much as correct code.
Everything you need to know about Technical tests.
Logical reasoning tests measure abstract thinking and pattern recognition, the ability to identify rules in sequences of shapes, symbols, and diagrams without language or numbers.
Cognitive ability tests measure general mental ability (GMA), the strongest single predictor of job performance. They combine numerical, verbal, logical, and spatial reasoning.
Data and analytical reasoning tests measure your ability to work with complex datasets, identify patterns, and draw evidence-based conclusions. Critical for data, consulting, and technology roles.