JPMorgan Chase Behavioral Interview Template — Data Analyst (Engineering)

What this interview covers: A structured, story-driven behavioral conversation aligned to JPMorgan Chase’s client-first, risk-and-controls, and teamwork culture. Interviewers expect STAR-form answers and will probe for depth, impact, and learning. Format and cadence (typical): 1:1 or small panel with a hiring manager and/or senior analysts; ~60 minutes with follow-up probes after each story. Candidates may have completed a prior HireVue screen; this live behavioral round focuses on judgment, ownership, and stakeholder influence in data-heavy work. Focus areas tailored to JPMorgan Chase: 1) Client impact and business value: How you translated analysis into decisions for internal or external clients; prioritizing high-value work under tight timelines (e.g., month/quarter-end, initiative launches). 2) Risk, controls, and data governance: Handling sensitive data, building validation/lineage checks, preventing control breaks, remediating data-quality issues, and documenting decisions for auditability. 3) Stakeholder management and communication: Partnering across lines of business; influencing without authority; simplifying complex findings for non-technical stakeholders (PMs, operations, finance, senior leaders). 4) Ownership and accountability: Navigating ambiguity, balancing multiple requests, escalating appropriately, learning from mistakes, and demonstrating bias toward action with measurable outcomes. 5) Collaboration across global teams and inclusion: Coordinating across time zones, seeking diverse viewpoints, and fostering an inclusive team environment. 6) Adaptability and continuous learning: Adopting new tools/processes (e.g., SQL/Python/BI), responding to evolving requirements/regulatory needs, and iterating based on feedback. 7) Ethics and integrity: Exercising sound judgment with confidential data; addressing conflicts of interest; doing the right thing under pressure. What interviewers listen for: Clear situation context, your specific role, concrete actions (technical and interpersonal), quantifiable results, control mindset, and evidence of reflection (what you’d do differently). Expect follow-ups that stress-test decisions, trade-offs, and stakeholder dynamics. Suggested story bank (prepare 6–8): - A time you caught or remediated a data-quality issue before it impacted a report/delivery. - Partnering with cross-functional stakeholders to define ambiguous metrics or KPIs. - Handling conflicting priorities from senior stakeholders and how you set expectations. - Delivering analysis under a hard deadline and the controls you put in place. - Communicating a complex finding to a non-technical audience and driving a decision. - Learning a new tool or process quickly to meet a business need. - Owning a mistake or near-miss, what you learned, and the permanent fix you implemented. Evaluation rubric (implicit): - Structure and clarity (STAR), outcome orientation, stakeholder empathy, risk/control awareness, collaboration, resilience, and growth mindset—all within the firm’s “How We Do Business” principles.