Interview questions for Tiger Analytics Senior Business Analyst
Hi everyone, this topic is for sharing Preparation guidelines and interview experience for Tiger Analytics Senior Business Analyst
The Senior Business Analyst role at Tiger Analytics involves a multi-stage assessment and interview process, designed to evaluate both technical skills and business proficiency. Below is a summary of the process and key points from the interviews you provided:
Assessment Test Rounds:
Round 1: Resume Shortlist
Recruiter/hiring team screens for relevant BA/analytics experience, SQL/Tableau skills, and domain exposure.
Round 2: Aptitude Test
Logical reasoning and statistics-based questions.
Round 3: Assignment Round
Tableau dashboard assignment to create an end-to-end dashboard with appropriate visuals and insights.
Given a real-world business case; asked to provide a structured problem approach, clarifying questions, solution and recommendation.
Technical Interview(s)
Focus areas varied across experiences: Tableau and SQL; ML and SQL; discussion of past projects and applied analytics.
One-on-One/Conversational Deep Dive
Follow-up discussion on the earlier case, probing assumptions, implications, risks, scalability, and implementation.
HR Interview
Usual HR interactions: role fit, expectations, salary discussion, logistical details.
Technical: SQL (Advanced)
Write a query using window functions to find the top N items per category (e.g., top 3 products by sales in each region).
Compute rolling/weekly metrics using window frames (e.g., 7-day moving average).
Remove duplicates while retaining the latest record per entity (using ROW_NUMBER/DENSE_RANK and filters).
Join multiple tables and handle NULLs appropriately; explain the impact of different join types on results.
Perform conditional aggregation (e.g., cohort metrics, funnel steps using CASE WHEN).
Pivot/unpivot data to reshape tables for reporting.
Identify and optimize slow queries (indexes, CTEs vs subqueries, refactoring for performance).
Technical: Tableau / Data Visualization
Build an interactive dashboard from a given dataset; explain your design choices and the insights you would present.
Create and use calculated fields, parameters, and level-of-detail (LOD) expressions; explain use cases for each.
Implement filters and dashboard actions to enable drill-down and guided analysis.
Choose appropriate chart types for different data/analyses and justify your choices.
Optimize dashboard performance (extracts vs live connections, minimizing quick filters, reducing marks).
Explain data blending vs joins in Tableau and when to use each.
Technical: Statistics & Probability
Perform a hypothesis test and interpret the p-value and confidence interval in a business context.
Explain correlation vs causation and how you would test/validate relationships.
Describe common distributions (normal, binomial) and where they apply in analytics problems.
Choose and justify measures of central tendency (mean vs median) in skewed datasets.
Technical: Machine Learning (as applicable)
Walk through an ML project you delivered: problem definition, data preparation, model selection, evaluation metrics, and business impact.
How do you select an algorithm for a classification/regression problem? Which metrics would you monitor and why?
How do you handle class imbalance and avoid overfitting? Describe validation strategies (e.g., cross-validation).
Outline your feature engineering approach for tabular data in a business analytics setting.
Case-Based / Business Problem-Solving
You’re given a real-world business case: define the problem, ask clarifying questions, outline your approach, and present a data-driven recommendation.
What assumptions are you making in your recommendation and how would you validate them?
Which KPIs would you track to measure impact and success for this case?
If new data contradicts your initial hypothesis, how would you adapt your solution?
What are the key risks and trade-offs in your recommendation, and how would you mitigate them?
How would you prioritize initiatives if resources are limited?
Business Analyst Scenario / Requirements Elicitation
How would you translate a vague business request into a structured analytics problem with clear deliverables?
What clarifying questions would you ask stakeholders at project kickoff?
How do you gather and prioritize requirements (e.g., MoSCoW/RICE) and manage scope?
How would you resolve conflicting stakeholder requirements and align on success criteria?
Aptitude & Logical Reasoning
Solve logical reasoning problems and pattern/sequence puzzles under time constraints.
Evaluate statements and determine valid conclusions (syllogisms, data sufficiency-style questions).
HR / Personality / Fit
Tell me about yourself and your experience relevant to the Senior BA role.
Why Tiger Analytics and why this role/team?
Describe a challenging stakeholder situation you handled and the outcome.
Share an example of leading cross-functional collaboration to deliver business impact.
Discuss your salary expectations, notice period, and location/relocation preferences.
Interview Preparation Tips:
Focus on Tableau, SQL, and statistics: practice dashboard building, LODs/parameters, and advanced SQL (window functions, performance tuning).
Brush up on case-based problem solving: structure your approach, ask clarifying questions, and tie recommendations to KPIs and impact.
Revise core ML concepts (if applicable to your profile) and be ready to discuss end-to-end ML projects and evaluation metrics.
Prepare real-world examples: highlight problem framing, stakeholder management, and measurable outcomes.
Refine your resume: keep it concise, role-aligned, and free of unnecessary personal details.
Communicate clearly: explain your thought process, defend assumptions, and remain flexible when presented with new information.
If you have attended the process from your campus, pls share your experiences here; Please follow guidelines
Application Process: Applied via LinkedIn before October 2022.
Interview Rounds:
Round 1 - Resume Shortlist:
Details: The initial round involved a resume screening process.
Outcome: Successfully shortlisted for the next round.
Round 2 - Aptitude Test:
Questions Asked: Logical reasoning and statistics-based questions.
Outcome: Cleared the aptitude test.
Round 3 - Assignment Round:
Details: A Tableau dashboard assignment was given.
Outcome: Completed the assignment successfully.
Round 4 - Coding Test:
Questions Asked: Advanced SQL coding questions.
Outcome: Passed the SQL coding test.
Round 5 - Technical Round:
Questions Asked: Questions focused on Tableau and SQL.
Outcome: Advanced to the next round.
Round 6 - HR Round:
Questions Asked: Usual HR interactions and salary discussion.
Outcome: Final round completed.
Preparation Tips:
Focus on Tableau, SQL, and statistics for the technical rounds.
Brush up on logical reasoning and data visualization concepts.
Practice advanced SQL queries and Tableau dashboard creation.
Conclusion:
The interview process was thorough and covered a wide range of topics relevant to the role. Preparing well for the technical aspects, especially Tableau and SQL, was crucial. The HR round was straightforward, focusing on fit and expectations. Overall, a great learning experience!
Application Process: Applied via the company website in April 2021.
Interview Rounds:
Round 1 - Technical:
Questions Asked: SQL basics with on-the-go questions during a screen share.
Your Approach: Focused on fundamental SQL queries and practiced real-time problem-solving.
Outcome: Successfully cleared the round.
Round 2 - Aptitude Test:
Questions Asked: Basic aptitude questions to assess analytical skills.
Your Approach: Solved problems methodically and ensured accuracy.
Outcome: Cleared the aptitude test.
Round 3 - Case Study:
Questions Asked: Application-based questions on Tableau and R.
Your Approach: Demonstrated proficiency in Tableau and R by solving practical problems.
Outcome: Advanced to the next round.
Round 4 - Interview:
Questions Asked: Deep dive into the case solution submitted earlier, lasting about 30 minutes.
Your Approach: Thoroughly explained the case solution and addressed follow-up questions.
Outcome: Cleared the final round.
Preparation Tips:
Prepare the basics of any query language, visualization tool, and statistical tool.
Be thorough with the case solution submitted in the case round.
Conclusion:
The interview process was comprehensive, covering technical skills, aptitude, and practical applications. Being well-prepared with the basics and the case study solution was key to success. Future candidates should focus on mastering these areas to perform well in the interview.
Application Process: After submitting a presentation on a case solution, I received a call for a Skype interview.
Interview Rounds:
Round 1 - Skype Interview:
Questions Asked: The interview covered a diverse set of topics, including statistics, analytical concepts, SQL, and pseudocodes.
Your Approach: I focused on explaining my thought process clearly and logically, especially for the analytical and SQL questions. For the pseudocode, I ensured my logic was sound and easy to follow.
Outcome: The interview went well, and I felt confident about my performance.
Preparation Tips:
Brush up on core statistical concepts and analytical problem-solving techniques.
Practice writing efficient SQL queries and pseudocode for common business scenarios.
Be prepared to explain your thought process step-by-step during the interview.
Conclusion:
Overall, the interview was a great learning experience. The diverse range of questions helped me gauge my strengths and areas for improvement. For future candidates, I’d recommend practicing a variety of analytical problems and being comfortable with explaining your solutions clearly.
Application Process: I applied via Naukri.com and was interviewed in October 2023.
Interview Rounds:
Round 1 - Technical Round:
Questions Asked:
What does a Business Analyst (BA) do?
Do you know SQL?
Your Approach: I explained the role of a Business Analyst, focusing on requirements gathering, stakeholder communication, and bridging the gap between business and IT. For SQL, I confirmed my knowledge and mentioned my experience with queries and databases.
Outcome: I passed this round.
Round 2 - One-on-one Round:
Questions Asked:
What does a BA do?
What is SQL?
Your Approach: I reiterated the BA role, emphasizing problem-solving and analytical skills. For SQL, I provided a brief definition and examples of its use in data analysis.
Outcome: I passed this round as well.
Preparation Tips:
Brush up on the core responsibilities of a Business Analyst.
Be clear about your SQL knowledge and how it applies to the role.
Practice explaining technical concepts in simple terms.
Conclusion:
The interview process was straightforward, with a focus on understanding the BA role and SQL. I felt confident in my answers, but I could have prepared more examples of my work to make my responses stronger. For future candidates, clarity and confidence in explaining your skills are key.
Application Process: Applied via a recruitment consultant in December 2023.
Interview Rounds:
Round 1 - Coding Test:
Questions Asked: Online SQL test with four questions.
Your Approach: Prepared by revising SQL concepts and practicing queries. Focused on optimizing solutions for efficiency.
Outcome: Cleared the round successfully.
Round 2 - Assignment Round:
Questions Asked: Take-home BI assignment with two questions.
Your Approach: Used BI tools to create visualizations and analyzed the given data thoroughly. Ensured clarity and accuracy in the deliverables.
Outcome: Awaiting results.
Preparation Tips:
Brush up on SQL concepts, especially query optimization.
Familiarize yourself with BI tools and data visualization techniques.
Practice solving real-world business problems using data.
Conclusion:
The interview process was smooth and well-structured. The SQL round tested technical skills, while the BI assignment assessed practical application. Would recommend practicing both SQL and BI tools extensively before applying.
Application Process: The application process began with a resume shortlist round, followed by technical and one-on-one interview rounds.
Interview Rounds:
Round 1 - Resume Shortlist Round:
Questions Asked: No specific questions were asked in this round. The focus was on reviewing the resume for relevant experience and skills.
Your Approach: Ensured the resume was concise, highlighting key skills and experiences relevant to the role of a Senior Business Analyst. Avoided including unnecessary personal details like photos, gender, age, or address.
Outcome: Successfully cleared the resume shortlist round and moved to the next stage.
Round 2 - Technical Round:
Questions Asked:
About business analyst scenario.
Your Approach: Prepared by reviewing common business analyst scenarios and case studies. Focused on structuring answers logically and demonstrating problem-solving skills.
Outcome: Cleared the technical round and advanced to the final interview stage.
Round 3 - One-on-one Round:
Questions Asked:
About business analyst scenario.
Your Approach: Used real-world examples to explain the scenario, emphasizing analytical thinking and decision-making processes.
Outcome: Successfully cleared the round and received positive feedback.
Preparation Tips:
Focus on refining your resume to highlight relevant skills and avoid unnecessary personal details.
Practice common business analyst scenarios and case studies to improve problem-solving and analytical skills.
Be prepared to discuss real-world examples to demonstrate your experience and approach.
Conclusion:
The interview process was structured and focused on assessing both technical and analytical skills. Preparing for common scenarios and ensuring a well-structured resume were key to success. Future candidates should emphasize their problem-solving abilities and practical experience in business analysis.
Application Process: I applied through a recruitment consultant in February 2023.
Interview Rounds:
Round 1 - Resume Shortlist:
Details: The recruiter reviewed my resume to ensure it matched the job requirements.
Outcome: I was shortlisted for the next round.
Round 2 - One-on-One Interview:
Questions Asked:
Financial products-based questions, such as CDS, IRS Bonds, etc.
IRS valuation and cash flow-based questions.
Currency swap structuring and concept-based questions.
Your Approach: I focused on explaining the concepts clearly and providing practical examples where applicable.
Outcome: I advanced to the next round.
Round 3 - One-on-One Interview:
Questions Asked:
Domain skills-based questions. The interviewer emphasized the impact of prior company brand names.
Your Approach: I highlighted my domain expertise and how my previous experience aligned with the role.
Outcome: The interview concluded positively, and I awaited further updates.
Preparation Tips:
Domain knowledge is crucial for this role. Focus on understanding financial products, valuation methods, and structuring concepts.
Be prepared to discuss your prior work experience in detail, as the company values brand names and domain expertise.
Conclusion:
The interview process was thorough and emphasized domain-specific knowledge. I found the questions challenging but fair. For future candidates, I recommend brushing up on financial products and being ready to discuss your prior work in detail. The company values clarity and practical understanding, so focus on those aspects during your preparation.
Application Process: [Application process details not provided]
Interview Rounds:
Round 1 - One-on-one Round:
Questions Asked:
Q1. One pager profile
Q2. Transaction and precedent comps
Your Approach:
For Q1, I prepared a concise one-pager summarizing my profile, highlighting key skills and experiences relevant to the role.
For Q2, I discussed my understanding of transaction and precedent comps, providing examples from my past work.
Outcome: [Result of this round not provided]
Preparation Tips:
Stay updated with IB (Investment Banking) analytics.
Focus on skills like Business Analysis, Secondary Research, Market Research, Factiva, Capital IQ, Competitive Intelligence, Industry Research, and Company Profiling.
Conclusion:
[Overall experience and final advice not provided]
Application Process: Applied through campus placement/online application (details not specified).
Interview Rounds:
Round 1 - Aptitude Test:
Questions Asked: Aptitude test with easy-level questions.
Your Approach: The test was straightforward, and I focused on accuracy and time management.
Outcome: Passed the round.
Round 2 - Technical Round:
Questions Asked: Basic SQL and Excel questions.
Your Approach: I revised SQL queries and Excel functions beforehand and answered confidently.
Outcome: Cleared the technical round.
Round 3 - HR Round:
Questions Asked: General HR questions, no salary negotiation involved.
Your Approach: I maintained a professional and positive demeanor throughout the conversation.
Outcome: Successfully cleared the HR round.
Preparation Tips:
Focus on basic SQL and Excel skills for the technical round.
Practice aptitude tests to improve speed and accuracy.
Be prepared for general HR questions and maintain a professional attitude.
Conclusion:
The interview process was smooth, but I would advise waiting for better opportunities with higher pay if possible. The experience was good, but the compensation might not be competitive compared to other offers in the market.
Application Process: I applied via a job portal and was interviewed in January 2024.
Interview Rounds:
Round 1 - Coding Test:
Questions Asked: It was a SQL assessment with two questions to solve.
Your Approach: I focused on writing efficient queries and ensuring accuracy in my solutions.
Outcome: Cleared the round successfully.
Round 2 - Case Study Round:
Questions Asked: Had to present a case study.
Your Approach: I structured my presentation logically, highlighting key insights and recommendations.
Outcome: Advanced to the next round.
Round 3 - Technical Round:
Questions Asked: A question related to the case study presented earlier.
Your Approach: I elaborated on my thought process and justified my approach.
Outcome: Cleared the round.
Round 4 - Case Study Round:
Questions Asked: Provided raw data and asked to derive insights and present them.
Your Approach: I analyzed the data thoroughly, identified patterns, and presented actionable insights.
Outcome: Final round cleared.
Preparation Tips:
Brush up on SQL for coding assessments.
Practice presenting case studies clearly and concisely.
Be prepared to derive insights from raw data and justify your findings.
Conclusion:
Overall, the interview process was thorough and tested both technical and analytical skills. Practicing case studies and SQL beforehand helped me perform well. For future candidates, focus on clarity in communication and logical structuring of your answers.
Application Process: Applied through an online job portal.
Interview Rounds:
Round 1 - Case-Based Interview:
Questions Asked: Given a business case and asked to provide a solution/recommendation. The case was related to a real-world business problem.
Your Approach: Tried to understand the problem thoroughly, asked clarifying questions, and structured my response logically. Focused on data-driven recommendations.
Outcome: Passed this round. The interviewer appreciated the structured approach.
Round 2 - Technical Interview (ML & SQL):
Questions Asked: Questions related to machine learning concepts and SQL queries. Also discussed past projects involving ML models.
Your Approach: Explained ML concepts clearly and wrote efficient SQL queries. Highlighted my experience with ML projects.
Outcome: Passed this round. The interviewer seemed satisfied with the technical depth.
Round 3 - Conversational Interview:
Questions Asked: More of a discussion about the case from Round 1, diving deeper into the solution and its implications.
Your Approach: Engaged in a back-and-forth discussion, defended my recommendations, and showed flexibility in adapting to new insights.
Outcome: Passed this round. The conversation was smooth and collaborative.
Preparation Tips:
Brush up on case-based problem-solving techniques.
Revise core ML concepts and SQL queries.
Practice explaining your thought process clearly and logically.
Conclusion:
Overall, the interview process was smooth and engaging. The case-based rounds were particularly interesting as they mimicked real-world scenarios. I could have prepared more on specific ML algorithms to answer more confidently. For future candidates, focus on structuring your thoughts and being clear in your explanations.