Canva

Assessment Rubric Overview: "Closest Random Points"

The "Closest Random Points" problem evaluates a candidate's proficiency in computational geometry, algorithm design, and optimization techniques. Specifically, it tests the ability to efficiently compute the squared shortest distance between pairs of points in a two-dimensional plane—a fundamental problem with applications in various fields such as computer graphics, spatial analysis, and machine learning.

Core Competencies and Skills:

• Algorithm Design and Optimization: Candidates should demonstrate the ability to design efficient algorithms, particularly those that can reduce the computational complexity of brute-force solutions.

• Computational Geometry: A solid understanding of geometric principles, including distance calculations and spatial data structures, is essential.

• Problem-Solving and Analytical Thinking: The ability to break down complex problems into manageable components and devise systematic solutions is crucial.

Behavioral Traits and Problem-Solving Approaches:

• Analytical Thinking: Interviewers will assess the candidate's approach to dissecting the problem, identifying patterns, and formulating a structured solution.

• Adaptability: The ability to consider and implement alternative solutions, such as utilizing spatial data structures or parallel processing, will be evaluated.

• Communication Skills: Clearly articulating the thought process, justifying design choices, and discussing trade-offs are key aspects of the assessment.

Assessment Process Expectations:

Canva's interview process is designed to be a two-way conversation, allowing candidates to showcase their skills and learn about the company. The process typically includes:

1. Initial Screening: A conversation with the Talent Acquisition team to discuss the candidate's background and the role.

2. Technical Interviews: These may involve coding challenges, system design discussions, and problem-solving exercises relevant to the role.

3. Take-Home Challenge: Candidates are given a challenge to complete in their own time, demonstrating their approach to real-world problems.

4. Final Interview: A comprehensive discussion with team members, including behavioral questions aligned with Canva's Skills Hiring Framework.

Throughout the process, Canva emphasizes a collaborative and supportive environment, encouraging candidates to be themselves and engage in open dialogue. As one candidate noted, "The recruiter is there to support you every step of the way, making you feel that they want you to be successful." (glassdoor.com)

Preparation Recommendations:

• Algorithm Practice: Engage in coding exercises that focus on algorithm optimization and computational geometry problems.

• Understand Spatial Data Structures: Familiarize yourself with data structures like k-d trees and their applications in nearest neighbor searches.

• Review Previous Work: Be prepared to discuss past projects that demonstrate your problem-solving abilities and technical expertise.

• Behavioral Interview Preparation: Reflect on experiences that showcase your adaptability, teamwork, and communication skills.

Evaluation Criteria and Technical Concepts:

• Efficiency: Solutions should aim to minimize time and space complexity, moving beyond brute-force approaches.

• Correctness: Ensure that the algorithm accurately computes the squared shortest distance for all input cases.

• Clarity: Present solutions in a clear and organized manner, with well-documented code and explanations.

• Innovation: Demonstrate creative problem-solving by considering and implementing alternative solutions.

Canva-Specific Expectations:

Canva values diversity of thought and experience, seeking candidates who bring unique perspectives and align with the company's core values. The company fosters a culture of continuous learning and adaptability, expecting candidates to embrace change and contribute to a collaborative environment. As one candidate shared, "The interview process was very considered... I felt at ease with the interviewers who were really easy to talk to and made the process feel less like an interview and more a chat to get to know each other." (glassdoor.com)

By focusing on these competencies and approaches, candidates can effectively prepare for the "Closest Random Points" problem and align with Canva's interview expectations.