Preparing for an interview at Leidos requires a balanced approach. Because the company serves diverse clients—ranging from federal agencies to commercial enterprises—your interviewers will look for both technical capability and strong professional maturity.

Role-related Knowledge – You must demonstrate a solid grasp of data analysis fundamentals, including data querying, cleaning, visualization, and statistical interpretation. Be ready to discuss the specific tools you use (such as SQL, Python, R, Power BI, or Excel) and explain why you choose them for various tasks.

Problem-solving Ability – Interviewers want to see how you think. When presented with a case study or a technical scenario, focus on structuring your thoughts logically. Walk the interviewer through your methodology step-by-step, explaining the assumptions you are making and how you validate your conclusions.

Time Management & Execution – Operating under tight deadlines is a common reality at Leidos. You should be prepared to discuss concrete strategies you use to prioritize tasks, track progress, and deliver high-quality analytical outputs on schedule.

Communication & Collaboration – As a Data Analyst, you will act as a bridge between data and operations. You must show that you can communicate complex analytical concepts clearly and build strong working relationships with diverse stakeholders, including scientists, billing managers, and program directors.

The interview process for a Data Analyst at Leidos is designed to be straightforward, efficient, and highly communicative. While the exact flow can vary slightly depending on the seniority of the role (such as Senior Data Analyst or SME Data Analyst) and the specific business unit, candidates generally experience a structured progression that balances technical assessment with behavioral evaluation.

Typically, the process begins with an initial screening by a recruiter or a hiring manager to review your background and discuss your interest in the company. Following this, you will proceed to one or more interview rounds. For some roles, this may involve a single, comprehensive panel interview with key team members, such as operations directors or billing managers. For other roles, particularly those requiring high collaboration, you may participate in a multi-stage process that includes a behavioral panel followed by an interactive case study interview alongside other candidates.

The visual timeline above outlines the typical stages a candidate goes through during the Leidos hiring process. Candidates should use this timeline to pace their preparation, ensuring they allocate ample time to practice both technical problem-solving and behavioral storytelling before reaching the panel stages.

To excel in your Leidos interviews, you must understand the specific areas where you will be evaluated. Interviewers will assess your capabilities across several core competencies.

Operational Problem Solving & Case Studies

This area evaluates your ability to apply structured analytical thinking to real-world operational scenarios. Leidos values analysts who can look at a business process, identify inefficiencies, and propose data-driven solutions.

Be ready to go over:

• Scenario-based prioritization – How you decide which data issues to tackle first when resources are limited.
• Collaborative analysis – Working with peers or stakeholders to dissect a problem during a case study.
• Structured walkthroughs – Explaining your step-by-step methodology clearly during hypothetical problem-solving exercises.
• Advanced concepts (less common) – Cross-functional operational alignment and predictive modeling for resource forecasting.

Example scenarios:

• "If you were handed a messy dataset containing billing discrepancies from multiple departments, how would you structure your investigation?"
• "Walk us through how you would design a dashboard to help operations managers track daily project deadlines."

Behavioral & Time Management

Because Leidos manages large-scale, deadline-driven programs, your ability to manage your time and adapt to structured environments is highly scrutinized.

Be ready to go over:

• Strict deadline management – Demonstrating your ability to deliver accurate work under tight timelines.
• Situational adaptability – How you handle shifting priorities or sudden changes in project requirements.
• Work style and interests – Showing alignment with Leidos values, including integrity, collaboration, and continuous learning.
• Advanced concepts (less common) – Managing stakeholder expectations when data-driven insights contradict established operational practices.

Example scenarios:

• "Describe a time when you had multiple competing deadlines. How did you organize your day to ensure nothing fell through the cracks?"
• "Tell me about a time you had to work with a difficult stakeholder to gather requirements for an analysis."

Technical Savviness & Tool Competency

Your technical skills must match the demands of the specific business unit you are applying to. Some teams focus heavily on business systems and billing data, while others require deep scientific or engineering data manipulation.

Be ready to go over:

• Data querying & manipulation – Writing efficient queries and handling data transformation tasks.
• Systems integration – Understanding how data flows between different enterprise systems and databases.
• Troubleshooting data discrepancies – Identifying and correcting errors in complex data pipelines.
• Advanced concepts (less common) – Cloud database architectures, secure government data environments, and automated ETL processes.

Example scenarios:

• "How do you ensure data integrity when merging datasets with inconsistent formatting or missing values?"
• "What is your approach to learning a brand-new analytical tool or software system that you have not used before?"

As a Data Analyst at Leidos, your day-to-day work will be dynamic and closely integrated with the operations of your assigned team. You will be responsible for managing the lifecycle of operational data, ensuring it is collected, processed, and analyzed accurately to support program goals.

Your primary responsibilities will include:

• Extracting, cleaning, and transforming large datasets from various internal and external databases.
• Developing and maintaining interactive dashboards, reports, and data visualizations to track key performance indicators (KPIs) and operational metrics.
• Collaborating with cross-functional team members, such as billing managers, operations directors, and scientists, to understand their data needs and deliver actionable insights.
• Conducting root-cause analyses on operational anomalies, billing discrepancies, or system performance issues.
• Documenting analytical methodologies, data sources, and business rules to ensure consistency and compliance across the organization.

You will often find yourself working on projects that require a high degree of precision, particularly when handling financial, billing, or compliance-related data. Your ability to produce error-free analyses is critical, as these outputs are frequently used to make strategic decisions or report directly to client stakeholders.