Leidos Behavioral Interview Template – Data Analyst (Engineering)

This behavioral interview evaluates how a Data Analyst operates in Leidos’s mission-focused, government‑contracting environment across Defense, Civil, and Health programs. Format: 60‑minute panel (hiring manager + senior analyst + program/technical lead) using STAR responses and scenario walkthroughs tied to real program constraints (e.g., working with FAA/DoD/HHS stakeholders, multi‑contractor teams, and regulated data). Focus areas specific to Leidos: - Mission mindset and customer orientation: aligning analytics to program objectives, contract deliverables, and measurable mission outcomes under schedule/budget constraints. - Security/compliance awareness: handling CUI/PII/HIPAA, need‑to‑know boundaries, data lineage/documentation for ATO/quality audits, and operating effectively when data access is restricted. - Collaboration in matrixed, multi‑contractor settings: partnering with PMOs, systems engineers, data stewards, and external vendors; navigating role clarity and communication paths common in federal programs. - Data quality and reliability under legacy/complex systems: triaging source issues, building trust with non‑technical stakeholders, and balancing speed vs. rigor for operational decisions. - Communication and storytelling: translating analysis for government audiences, writing concise status reports, and tailoring insights to executives vs. operators. - Adaptability and ethics: responding to changing requirements, recompetes, or shifting priorities while upholding integrity, documentation standards, and traceability. What interviewers look for: - Clear STAR structure, quantifiable outcomes, and lessons learned. - Evidence of ownership in ambiguous environments (e.g., incomplete requirements, evolving data contracts). - Proactive risk/issue management (escalation paths, trade‑offs, and customer impact). - Respect for security, compliance, and ethical data use in day‑to‑day decisions. Example prompts you should be ready for (behavioral, not technical): - Describe a time you delivered an analysis that directly supported a customer mission milestone or contract deliverable. How did you handle competing priorities and what changed because of your work? - Tell us about a situation where security or privacy constraints limited your analysis. What guardrails did you apply, and how did you still deliver value? - Give an example of resolving a critical data quality issue in a legacy or multi‑source environment. How did you communicate risk to program leadership and the customer? - Walk through a conflict between stakeholder groups (e.g., program management vs. operations). How did you align them and protect mission outcomes? - Share a time you documented data lineage/assumptions for audit or ATO‑related review. What was the impact on trust and reuse? Candidate guidance: Prepare 4–6 STAR stories mapped to the themes above; bring one example each for mission impact, security/compliance, multi‑team collaboration, and data quality triage. Keep answers concise (2–3 minutes each) with concrete metrics and customer impact.