Palantir

Assessment Rubric Overview: "Romanizer" Problem

The "Romanizer" problem evaluates a candidate's proficiency in algorithm design, data structures, and numerical systems, specifically focusing on converting integers to Roman numerals. This task assesses the candidate's understanding of Roman numeral conventions, their ability to implement efficient algorithms, and their attention to detail in handling edge cases.

Core Competencies and Skills Evaluated:

• Algorithm Design: Ability to devise an efficient algorithm that accurately converts integers to Roman numerals, considering both time and space complexity.

• Data Structures: Proficiency in selecting and utilizing appropriate data structures to facilitate the conversion process.

• Numerical Systems Understanding: Deep knowledge of Roman numeral rules, including the use of subtractive notation (e.g., IV for 4, IX for 9) and the correct ordering of symbols.

• Edge Case Handling: Skill in identifying and managing potential edge cases, such as the smallest (1) and largest (3999) valid integers, and ensuring the algorithm's robustness.

Behavioral Traits and Problem-Solving Approaches Assessed:

• Analytical Thinking: Demonstrated ability to break down the problem into manageable components and develop a structured approach to the solution.

• Attention to Detail: Meticulousness in implementing the conversion rules and ensuring accuracy in the final output.

• Adaptability: Willingness to adjust the approach based on feedback or new insights during the problem-solving process.

• Communication: Clarity in articulating the thought process, explaining the chosen algorithm, and discussing potential optimizations.

Assessment Process Expectations:

Candidates can anticipate a multi-stage interview process, including:

1. Initial Screening: A coding challenge or technical interview focusing on algorithmic problem-solving skills.

2. Technical Interviews: In-depth discussions and live coding sessions to assess the candidate's approach to the problem, coding proficiency, and understanding of relevant concepts.

3. Behavioral Interviews: Evaluations of cultural fit, communication skills, and alignment with Atlassian's values.

Feedback is typically provided after each interview stage, with a comprehensive review at the conclusion of the process. Candidates should be prepared for a thorough evaluation of both technical and interpersonal skills.

Preparation Recommendations:

• Algorithm Practice: Engage in exercises that involve converting between different numerical systems and implementing algorithms with varying time and space complexities.

• Data Structures Review: Study data structures that facilitate efficient mapping and retrieval operations, such as hash maps and arrays.

• Roman Numeral Study: Familiarize yourself with the complete set of Roman numeral symbols and their combinations, including subtractive notation.

• Edge Case Identification: Practice identifying and handling edge cases in numerical algorithms to ensure robustness.

Evaluation Criteria and Technical Concepts:

• Correctness: Ensuring the algorithm produces accurate Roman numeral representations for all valid inputs.

• Efficiency: Optimizing the algorithm to handle the full range of input values within acceptable time and space limits.

• Code Quality: Writing clean, readable, and maintainable code with appropriate comments and documentation.

• Problem-Solving Approach: Demonstrating a logical and systematic approach to solving the problem, including clear articulation of the thought process.

Atlassian-Specific Expectations and Cultural Fit Considerations:

Atlassian values collaboration, transparency, and a commitment to continuous improvement. Candidates should exhibit:

• Team Collaboration: Ability to work effectively in team settings, sharing knowledge and supporting peers.

• Continuous Learning: A proactive approach to learning new technologies and methodologies.

• Customer Focus: Understanding the end-user perspective and striving to create user-friendly solutions.

• Cultural Alignment: Demonstrating alignment with Atlassian's core values and mission.

By focusing on these areas, candidates can prepare effectively for the "Romanizer" problem and align with Atlassian's expectations during the interview process.