Business Analyst Interview Questions (2025) – Tiger Analytics Guide

Candidates preparing for business analyst interview questions at Tiger Analytics should understand that this role demands both strong analytical rigor and exceptional stakeholder communication. In this guide, we’ll walk through the key components of the process, from case assessments to behavioral evaluations, so you know exactly what to expect and how to excel.

Tiger Analytics Business Analysts partner closely with clients to translate complex data into actionable insights, often under tight timelines and evolving requirements. This client-first environment rewards those who can balance technical SQL and Excel skills with the ability to tell a compelling story—so ahead of diving into the stages, let’s explore what makes this role unique.

Role Overview & Culture

A Business Analyst at Tiger Analytics designs and executes data-driven solutions that inform strategic decisions for Fortune 500 clients. You’ll gather requirements, perform deep-dive analyses, and align findings with cross-functional teams, all while embodying the firm’s values of customer-centricity, agility, and continuous improvement. The culture encourages rapid experimentation and empowers analysts to own both the process and the outcomes, ensuring you have a direct impact on client success.

Why This Role?

Tiger Analytics Business Analysts enjoy visibility across domains—from retail to financial services—working on high-stakes projects that drive tangible business results. Competitive compensation and clear promotion pathways reward high performers, with opportunities to advance into Product or Strategy roles. Ready to learn how to navigate the interview process? Let’s break down each stage.

Here’s a concise overview of the Tiger Analytics hiring journey for Business Analysts, designed to assess both your technical acumen and client-facing skills.

Application & Recruiter Screen

In this initial stage, a recruiter reviews your résumé for relevant project experience and schedules a call to discuss your background, motivations, and salary expectations. You’ll be evaluated on how clearly you articulate past analyses and your enthusiasm for client-facing work.

Aptitude / Case Assessment

Next, you’ll complete an analytical or logical-reasoning assessment, typically involving SQL queries or brain-teaser cases. This timed exercise gauges your problem-solving speed and accuracy under pressure.

Technical / Domain Interview

The technical round tests your proficiency in SQL, Excel, or process-mapping tools through live quizzes or take-home problems. Interviewers look for clean, efficient solutions and clear explanations of your methodology.

Behavioral & Stakeholder Simulation

In a role-play scenario, you’ll navigate conflicting requirements from mock stakeholders, demonstrating your communication style, prioritization framework, and ability to drive consensus. This stage highlights your agility and customer-centric approach.

Hiring Committee & Offer

Finally, a panel consolidates feedback and calibrates compensation based on level. Expect a 48-hour feedback cycle, after which you’ll receive an offer package outlining base, bonus, and potential equity.

Behind the Scenes

Tiger Analytics strives for rapid, transparent feedback, with a 48-hour target for interview outcomes and weekly hiring committee reviews to ensure consistency across candidates.

Differences by Level

Junior analysts focus primarily on core analysis skills and tool proficiency, while senior candidates face a strategic case study presentation and deeper discussions of stakeholder impact.

Now that you’ve seen each stage, you’re ready to tackle the most common business analyst interview questions that follow.

Here’s what to expect when you sit down for business analyst interview questions at Tiger Analytics. We’ll break them into three core categories to help you focus your prep.

Coding / Technical Questions

This section tests your hands-on data skills with SQL or Excel. You might be asked to write queries that join multiple tables, build pivot tables, or perform window-function calculations. For each sample task, explain why interviewers care (e.g., assessing your ability to manipulate data efficiently), how to approach the problem step by step, and provide a concise illustration of a correct solution.

1. How would you write a SQL query that returns the second-highest salary in the engineering department, correctly skipping ties for the top salary?

   Interviewers use this classic window-function prompt to see whether you know dense rank vs. row_number and can reason through edge-cases like duplicate maximums. It also reveals your ability to express business rules in SQL (“skip co-leaders, pick the next distinct value”). Because Business Analysts at Tiger frequently validate compensation or sales outliers for clients, the team wants proof you can craft concise, performant queries that mirror real-world reporting needs.

2. Given an integer list 0 … n with one value missing, how would you code a function that returns the missing number in O(n) time?

   This question checks your comfort with basic algorithmic reasoning and data-quality diagnostics: summation or XOR tricks surface quickly if you think analytically about patterns instead of brute-force searches. Business analysts often reconcile incomplete transactional feeds; the exercise shows you can identify gaps efficiently and explain the logic behind your solution to engineering partners.

3. In a single pass, how could you locate the indices of two numbers that sum to a target value in an array?

   Hash-map solutions demonstrate you understand time/space trade-offs and can optimize for O(n) performance. Tiger Analytics expects analysts to prototype quick data-checks or transformation scripts—your ability to choose the right data structure (dictionary look-ups over nested loops) tells interviewers you’ll write scalable code when wrangling large client datasets.

4. What straightforward algorithm would you use to decide whether an input string is a palindrome?

   This lightweight coding prompt validates your attention to edge cases (case sensitivity, punctuation) and your clarity in explaining step-by-step logic. Even though analysts are not full-time engineers, Tiger looks for teammates who can script small quality-of-life utilities or feature-engineering helpers without over-engineering the solution.

5. How would you simulate two overlapping nightly jobs to estimate the firm’s annual outage cost, and how might you instead derive the cost analytically with probability?

   The scenario gauges statistical thinking and business storytelling: first build a Monte-Carlo to generate an expected value, then articulate a theoretical calculation (5 hours window × overlap probability). Tiger’s clients lean on analysts to translate stochastic processes into dollar impacts, so the panel wants to see fluency in both simulation and closed-form reasoning.

6. What SQL logic would you write to flag whether each user’s subscription period overlaps any of their prior completed subscriptions?

   This overlap-detection task uncovers your ability to work with date math, self-joins, and non-trivial EXISTS clauses—skills vital for churn and retention analysis. Interviewers look for clear assumptions (e.g., inclusive vs. exclusive end dates) and performance awareness when tables grow to millions of rows.

7. How would you calculate “first-touch” marketing attribution for every user who converted, using only session-level and user-session mapping tables?

   Proper ranking, grouping, and joining show that you grasp lifecycle funnels and can translate messy web-analytics schemas into actionable attribution metrics. Tiger’s Business Analysts frequently advise on media-mix allocations; nailing this question signals you can own those analyses end-to-end.

8. Suppose you had to prototype a rudimentary random-forest-style classifier without scikit-learn—how would you structure the trees and aggregate the votes?

   While analysts are not expected to build production ML, Tiger values conceptual depth: you should outline data partitioning, entropy/gini splits, and majority voting, then discuss why true ensembles outperform single trees. Being able to sketch a manual implementation shows you can sanity-check model outputs and communicate mechanics to non-technical stakeholders.

9. Using window functions, how would you find the two students whose SAT scores are closest together, breaking ties alphabetically on names?

   This problem tests your skill in self-joining or lead/lag techniques to compute pairwise differences without quadratic scans. It mirrors real score-band or price-band analyses you’ll perform for education or retail clients, so demonstrating an elegant, scalable solution is crucial.

10. Describe how you would perform simulation sampling from a standard normal distribution and return the sample to downstream analysts.

    The prompt checks whether you know common numpy/pandas approaches, can discuss seeding for reproducibility, and understand when bootstrapping vs. theoretical sampling is appropriate. Tiger analysts often generate synthetic data to stress-test dashboards; the interviewers want assurance you can produce statistically valid samples and explain their limitations.

Business Case / Requirements Questions

In case-study rounds, you’ll work through mini business problems—such as redesigning an e-commerce checkout flow. Expect questions around breaking down user stories, applying prioritization frameworks like MoSCoW or RICE, and conducting gap analyses. Interviewers look for structured thinking, clear rationale for feature trade-offs, and an ability to align your solution to business objectives.

1. Given three candidate Lyft cancellation fees — $1, $3 and $5 — how would you design an analysis or experiment to recommend the optimal price point?

   This scenario probes your A/B-testing intuition and sensitivity-analysis skills. You should outline success metrics (gross profit, rider retention, driver utilization) and discuss stratified randomization to avoid geographic or temporal confounding. Explaining how you’d balance statistical power with customer-experience risk demonstrates commercial judgment. Tiger’s consulting teams frequently guide clients on pricing levers, so they need analysts who view experiments through both revenue and user-trust lenses.

2. When testing “close-friends” stories, how would you build control and treatment groups that correctly account for network effects among users who follow one another?

   Network-effect questions distinguish solid experimenters from great ones. You’re expected to mention cluster randomization (e.g., ego-networks), spill-over measurement, and potentially graph cut techniques. The panel looks for recognition that independent-and-identically-distributed assumptions break when friends influence each other’s story behavior. Showing you can articulate mitigations signals you can run trustworthy tests on social platforms or marketplaces.

3. How would you value the benefit of renewing an expiring streaming license for a hit TV show that has been on a streaming platform for a year?

   This question blends SQL-based cohort work with finance-style LTV modeling. Interviewers expect you to segment incremental view time, churn reduction, referral lift, and substitution effects versus other content. Discussing counterfactuals (what users watch if the show leaves) and the net present value of retention upsides shows end-to-end business acumen. Tiger Analytics values analysts who turn messy engagement logs into defensible dollar estimates for content decisions.

4. With limited wildlife counts, how would you estimate the number of deer living inside a national-park’s borders?

   Estimation challenges test your ability to combine sparse data with statistical methodology. You might invoke mark-and-recapture, aerial transects, or Bayesian hierarchical models that blend field observations with habitat density priors. Explaining sampling error, confidence intervals, and data-collection costs demonstrates consultative rigor. Because Tiger tackles domain-agnostic projects, they look for analysts who can design practical measurement frameworks in unfamiliar problem spaces.

5. Using company-wide spend data, how would you decide which retailer or brand should be the next co-branded partner credit card?

   The interviewer is assessing market-basket savvy and opportunity sizing. Outline segmentation of spend, overlap analysis with current card portfolios, projected interchange revenue, and cannibalization risks. Discuss qualitative factors (brand fit, negotiation leverage) alongside quantitative metrics (share-of-wallet lift). Tiger Analytics values analysts who fuse exploratory SQL with business-strategy storytelling.

6. Why might the VP of Sales be mis-interpreting a plot that shows agents receiving 3× more leads in month 3 and claiming this proves additional leads drive retention?

   Here you must spot survivorship and cohort biases. Explain how high-performing agents both stay longer and naturally receive more leads, creating reverse causality. Proposing a causal inference framework—randomized lead allocation or difference-in-differences—shows that you can push back on stakeholder conclusions diplomatically. Such critical thinking is central to Tiger’s advisory style.

7. An online food ordering company is launching in NYC and Charlotte; how would you build a dasher-selection framework, and would the criteria differ between the two markets?

   The prompt evaluates multi-factor decision design—supply-demand forecasts, driver ratings, travel-time models, and local regulations. Showing you can tailor weighting (e.g., traffic congestion priority in NYC, geographic coverage in Charlotte) proves context sensitivity. Tiger’s clients span regions and industries; adaptability in metric selection is therefore prized.

8. Which metrics would you monitor to quantify ride-sharing demand, detect high-demand/low-supply imbalance, and set alert thresholds?

   You should mention request-to-completion ratio, surge multiplier frequency, pickup-wait times, and abandonment rate, then propose statistical control limits or anomaly-detection bands. The answer reveals whether you think systematically about leading vs. lagging indicators and real-time dashboards. Such metric frameworks are core deliverables in Tiger engagements.

9. Using monthly price, churn, and tenure estimates, derive and explain the formula for average customer lifetime value at a SaaS firm.

   The interviewer wants to confirm fluency with retention math (LTV ≈ ARPU × 1/churn or more granular survival curves). Discuss sensitivity to churn-rate uncertainty and the advantage of cohort-level over single-number LTV. Tiger’s analytics work often feeds financial planning; clear articulation of assumptions and limitations distinguishes strong candidates.

Behavioral / Culture-Fit Questions

Behavioral prompts explore how you handle conflict, negotiate with stakeholders, and take ownership of projects. Preparing STAR or CAR-formatted responses is ideal: describe the Situation or Challenge, the Actions you took, and the Results achieved. Focus on examples that highlight your client empathy, communication skills, and ability to drive consensus in cross-functional teams.

1. Can you describe a recent data project you led, and what specific hurdles—technical, stakeholder-related, or timeline—made it particularly challenging?

   Tiger Analytics likes to see end-to-end ownership: defining scope, wrangling messy data, choosing the right analytical techniques, and driving business impact. Your answer should surface how you balanced speed against rigor and how you escalated or unblocked issues. Highlighting root-cause analysis and a measurable outcome (e.g., revenue lift, cost savings) proves you don’t just “build the model” but translate insights into action. Emphasize lessons learned, because consultants must recycle past experience into future engagements.

2. What practical steps have you taken to make complex data findings accessible to non-technical business users?

   Tiger’s analysts constantly distill statistics for executives, so interviewers want stories about visualization choices, layered storytelling, and self-serve dashboards. Mention tailoring KPIs to personas, using analogies, or A/B testing different report formats. Discuss how you gathered feedback to iterate on clarity and usability. Showing empathy for the audience signals you can drive adoption, not just deliver slide decks.

3. How would your current manager describe your three greatest strengths and your key development areas, and how are you actively addressing those gaps?

   The firm values self-awareness and a growth mindset. Framing strengths around client impact—e.g., translating vague asks into analytic requirements—demonstrates consulting readiness. For weaknesses, focus on concrete improvement plans (courses, mentoring, process tweaks) rather than generic flaws. Tiger interviewers listen for honesty without self-sabotage: acknowledge limits while proving you seek continuous up-skilling.

4. Tell us about a time you struggled to communicate an analytical recommendation to stakeholders and how you eventually won them over.

   Tiger projects often involve skeptical business owners; they need analysts who can reframe insights in stakeholder language. Walk through the situation, the mis-alignment, and the tactics you used—storytelling with visuals, quantifying business value, or running a quick pilot—to bridge the gap. Emphasize listening and iteration rather than one-way persuasion. Ending with a concrete business outcome (decision made, process changed) shows real influence.

5. What attracted you to Tiger Analytics, and how does this role align with your long-term career goals?

   Interviewers are gauging cultural fit and commitment to consulting life. Cite the firm’s reputation for solving open-ended problems across industries, its data-first culture, and opportunities to own client relationships early. Tie those attributes to your personal trajectory—e.g., wanting breadth of domain exposure or a fast track to thought leadership. A customized answer signals you’ve done more than skim the website.

6. When juggling overlapping client deliverables, how do you prioritize tasks and keep yourself—plus cross-functional teammates—organized?

   Strong answers mix frameworks (effort-impact, SLA deadlines, critical-path mapping) with tooling (Kanban boards, calendar blocks) and proactive communication. Tiger expects analysts to self-manage in high-pressure settings; discuss how you surface risks early and negotiate scope when needed. Highlight one example where prioritization avoided downstream rework or client dissatisfaction. Show that you balance analytical depth with pragmatic time management.

7. How have you handled a situation where a data insight contradicted senior leadership’s intuition, and what was the final outcome?

   In consulting, analysts often deliver uncomfortable truths. Explain how you validated the data, prepared evidence in business terms, and created alignment without bruising egos. Mention any compromise or follow-up experiment that de-risked the recommendation. This demonstrates diplomacy and backbone—key traits Tiger seeks for client-facing roles.

8. Describe a time you coached a less-experienced teammate through a complex analysis while still meeting a tight deadline. What did you delegate, and what did you retain?

   Senior analysts must multiply impact through mentorship. Lay out how you assessed the junior’s skills, provided frameworks or templates, and instituted check-ins to maintain quality. Note the final business impact and how the colleague’s capabilities grew. Tiger values leaders who can scale themselves across multiple concurrent engagements.

Before diving into specific questions, spend a moment mapping out your study plan for business analyst interview questions.

Study the Company & Domain

Research the industry and Tiger Analytics’ client verticals. Connect your past projects to relevant business problems they solve, demonstrating domain fluency from the first moment.

Master Core Question Types

Allocate roughly 40% of your prep to technical drills (SQL, Excel), 40% to business-case frameworks and practice, and 20% to behavioral storytelling. This balance ensures you’re ready for every round.

Think Out Loud & Ask Clarifying Questions

During practice sessions, verbalize your thought process and don’t hesitate to ask follow-up questions. This shows your interviewers you’re structured, thorough, and client-focused.

Brute Force → Optimize

For coding or case tasks, outline a simple, brute-force solution first, then refine it to a more efficient or polished approach. Recruiters appreciate candidates who can iterate quickly.

Mock Interviews & Feedback

Run timed mock interviews—20 minutes per case—and solicit honest feedback. Recording your sessions can help pinpoint areas to improve in both content and delivery.

Mastering business analyst interview questions means blending strong technical chops with structured problem-solving and compelling storytelling. By following this guide—practicing mock interviews, studying the role’s domain, and leveraging community resources—you’ll be well on your way to success.

For further support, explore our Learning Paths or schedule a mock interview today. Good luck, and check out Hoda Noorian’s success story for inspiration!