About Quantiphi
Company Description
Quantiphi is a leading advanced analytics and artificial intelligence company that specializes in providing innovative solutions to complex business problems. Founded with a vision to transform data into actionable insights, Quantiphi harnesses the power of machine learning, data science, and big data technologies to enable organizations to leverage their data for better decision-making. The company prides itself on a collaborative and inclusive work culture that encourages creativity, continuous learning, and professional development. Employees at Quantiphi enjoy a dynamic work environment where teamwork and open communication are highly valued, fostering a sense of belonging and shared purpose. The company also emphasizes work-life balance, offering flexible working arrangements to its diverse workforce.
Data Scientist Interview Questions
Q1: What is your experience with statistical modeling and how have you applied it in your previous projects?
In my previous role as a Data Scientist, I utilized statistical modeling techniques such as regression analysis and time series forecasting to predict customer behavior and sales trends. I applied these models to analyze historical data, leading to actionable insights that improved business strategies.
Q2: Can you explain the difference between supervised and unsupervised learning?
Supervised learning involves training a model on a labeled dataset, where the outcome is known, to make predictions. Unsupervised learning, on the other hand, involves analyzing data without labeled outcomes, identifying patterns or groupings within the data, such as clustering.
Q3: How do you approach feature selection in a machine learning model?
I approach feature selection by first understanding the business problem and the data available. I use techniques such as correlation analysis, recursive feature elimination, and regularization methods to identify the most relevant features that contribute to the model's performance while avoiding overfitting.
Q4: Describe a challenging data project you worked on and how you overcame the obstacles.
One challenging project involved cleaning a large dataset with numerous missing values and outliers. I overcame this by employing data imputation techniques for missing values and using robust statistical methods to identify and treat outliers, which ultimately improved the model's accuracy.
Q5: What tools and programming languages are you proficient in for data analysis?
I am proficient in Python and R for data analysis and modeling, and I frequently use libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow. I also have experience with SQL for database queries and data manipulation.
Machine Learning Engineer Interview Questions
Q1: What experience do you have with deploying machine learning models into production?
I have experience deploying machine learning models using cloud platforms like AWS and Azure. I have utilized tools such as Docker and Kubernetes for containerization, ensuring that models can be easily scaled and managed in a production environment.
Q2: Can you explain the concept of overfitting and how to prevent it?
Overfitting occurs when a model learns noise in the training data rather than the actual pattern, resulting in poor performance on unseen data. To prevent overfitting, I use techniques such as regularization, cross-validation, and pruning in decision trees.
Q3: What machine learning frameworks are you familiar with?
I am familiar with several machine learning frameworks, including TensorFlow, Keras, and PyTorch. Each framework has its strengths, and I choose the one that best fits the project requirements.
Q4: How do you ensure the model's performance post-deployment?
I monitor the model's performance using metrics such as accuracy, precision, and recall. I also implement feedback loops that allow for retraining and model updates based on new data to maintain performance over time.
Q5: Describe a project where you used deep learning techniques.
In a recent project, I developed a convolutional neural network (CNN) for image classification. I preprocessed the images, built the CNN architecture, and used data augmentation to enhance model robustness. The model achieved a high accuracy rate on the test set.
Data Analyst Interview Questions
Q1: How do you approach data visualization in your reports?
I prioritize clarity and effectiveness in data visualization by using tools like Tableau and Power BI. I select appropriate visual formats—such as bar charts, line graphs, or heat maps—tailored to the data and the audience's needs to convey insights effectively.
Q2: What experience do you have with SQL for data extraction and analysis?
I have extensive experience using SQL to query databases, perform joins, and aggregate data for analysis. I am proficient in writing complex queries to extract meaningful insights from large datasets efficiently.
Q3: Can you explain how you ensure data accuracy and integrity in your analyses?
I ensure data accuracy by implementing validation checks during data collection and preprocessing phases. I also cross-verify data with source systems and conduct regular audits to maintain integrity throughout the analysis process.
Q4: Describe a time when your analysis influenced a business decision.
I conducted an analysis on customer churn rates, identifying key factors that contributed to customer retention. My findings led to the implementation of targeted marketing strategies, resulting in a 15% decrease in churn over the next quarter.
Q5: What tools do you use for data analysis and reporting?
I primarily use Excel for data manipulation, SQL for database queries, and Tableau for data visualization. I also utilize programming languages like Python for more complex analyses and automation tasks.
Data Engineer Interview Questions
Q1: What is your experience with ETL processes, and can you describe a pipeline you have built?
I have extensive experience designing and implementing ETL processes using tools like Apache NiFi and Talend. I built a data pipeline that ingested data from various sources, transformed it for analysis, and loaded it into a data warehouse, ensuring data quality and consistency.
Q2: How do you manage and optimize large-scale data storage solutions?
I manage large-scale data storage by utilizing cloud platforms like AWS S3 and Azure Data Lake. I optimize storage by implementing partitioning strategies and lifecycle policies to manage data retention efficiently, ensuring cost-effectiveness and performance.
Q3: What programming languages and frameworks are you proficient in for data engineering?
I am proficient in Python and Java for data engineering tasks. I also have experience with Apache Spark for distributed data processing, which allows me to handle large datasets effectively.
Q4: Can you explain the importance of data modeling in data engineering?
Data modeling is crucial as it defines the structure of data and how it can be stored, accessed, and managed. It ensures that data is organized efficiently, facilitating easier data retrieval and analytics while maintaining data integrity.
Q5: Describe a challenging data engineering project you worked on and how you approached it.
I worked on a project that required integrating data from multiple sources with different formats. I approached this challenge by designing a flexible ETL framework that could accommodate various input formats, using schema mapping and transformation rules to standardize the data for analysis.
Conclusion Interview Questions
Quantiphi offers a vibrant and innovative work environment where professionals can thrive in data-driven roles. The interview questions provided for various job roles aim to help candidates prepare effectively and demonstrate their expertise in the fields of data science, machine learning, data analysis, and data engineering.
Company Background and Industry Position
Quantiphi, headquartered in the United States with a strong global footprint, has carved a niche as a leader in the intersection of artificial intelligence, cloud computing, and big data analytics. The company’s evolution from a boutique AI startup to a trusted partner for Fortune 500 firms marks its impressive trajectory within the tech-driven consulting space. What sets Quantiphi apart is its specialized focus on delivering AI-powered solutions that are deeply tailored to industries such as healthcare, insurance, media, and retail.
In a marketplace crowded with data science service providers, Quantiphi stands out by marrying advanced research with pragmatic business applications. This dual focus not only enhances client value but also shapes the kind of talent they seek during recruitment—professionals who are not just coders but problem solvers.
How the Hiring Process Works
- Application and Resume Screening: Quantiphi’s recruiters first sift through applications using a blend of automated tools and manual review. They prioritize candidates demonstrating both technical skill and domain understanding relevant to the job role. This stage weeds out generic applicants and spotlights those whose profiles align closely with strategic priorities.
- Online Assessment: Most technical roles require candidates to clear an online test. Unlike traditional exams focused solely on coding speed, Quantiphi’s tests assess problem-solving skills, algorithmic thinking, and sometimes domain-specific knowledge. The aim here is to simulate real-world challenges rather than just gauge rote memorization.
- Technical Interviews: Successful candidates proceed to multiple rounds of technical interviews. These sessions are less about grilling trivia and more about collaborative problem solving. Expect discussions on data structures, machine learning concepts, system design, and project experiences. Interviewers often dive deep to understand candidates’ thought processes rather than just their final answers.
- HR Interview: The final hurdle usually involves a conversation with HR personnel. This isn’t just about cultural fit but also clarifying candidate expectations around salary, work environment, and growth aspirations. The HR round helps both sides ensure alignment beyond technical capability.
- Offer and Onboarding: Candidates who clear all rounds receive an offer detailing compensation and role specifics. Onboarding is structured to ramp new hires quickly through training, mentorship, and immersion in live projects.
This layered approach underscores Quantiphi’s commitment to quality hires, ensuring candidates aren’t just technically competent but also aligned with the company’s mission and values.
Interview Stages Explained
Online Assessment: The First Filter
This stage typically includes coding challenges on platforms like HackerRank or Codility, designed to evaluate a candidate’s command over programming languages such as Python, Java, or C++. But more than just coding syntax, the problems test algorithmic thinking, optimization skills, and sometimes data manipulation capabilities. For data science roles, expect questions on statistics, probability, and SQL querying.
Technical Interview Rounds: Deep Diving into Skills
The technical rounds are often split between general coding and role-specific expertise. For example, a machine learning engineer might face questions about model evaluation metrics or feature engineering, while a software engineer could be challenged with system design scenarios. Interviewers are keen observers of how candidates approach problems—do they ask clarifying questions? Do they communicate ideas clearly? These rounds simulate scenarios candidates might encounter on the job.
HR Round: Beyond Skill Sets
Contrary to the stereotype of perfunctory HR calls, Quantiphi’s HR discussions tend to be open dialogues. Candidates are encouraged to express their career goals, discuss flexibility preferences, and clarify role expectations. This round is crucial in determining if the candidate’s mindset meshes with Quantiphi’s culture of innovation, collaboration, and continuous learning.
Examples of Questions Candidates Report
- Technical Coding: “Write a function to find the longest substring without repeating characters.”
- Data Science: “How would you approach handling imbalanced datasets in a classification problem?”
- System Design: “Design a recommendation system for an e-commerce platform.”
- Behavioral: “Describe a situation where you had to overcome a significant challenge on a project.”
- HR: “Where do you see yourself in five years, and how does Quantiphi fit into that vision?”
Eligibility Expectations
Quantiphi maintains a selective criterion, typically seeking candidates with a strong academic background in fields like computer science, statistics, or engineering. For entry-level roles, fresh graduates with solid internships in data analytics or software development stand a chance. Mid to senior-level positions generally require 3-8 years of relevant experience and proven project delivery.
The company values not just degrees but demonstrable skills—think open-source contributions, published research, or hackathon wins. For specialized roles in AI and machine learning, advanced degrees or certifications can provide an edge but aren’t mandatory if the candidate’s portfolio speaks volumes.
Common Job Roles and Departments
Quantiphi’s recruitment spans diverse roles, each demanding varied skill sets and domain familiarity. Here’s a glimpse:
- Data Scientist: Crafting models that turn raw data into actionable insights across industries.
- Machine Learning Engineer: Building scalable algorithms and deploying AI services on cloud platforms.
- Software Developer: Developing robust applications that integrate with AI pipelines.
- Cloud Solutions Architect: Designing infrastructure capable of supporting complex AI workloads.
- Product Manager: Bridging technical teams and clients to deliver AI products aligned with business goals.
Compensation and Salary Perspective
| Role | Estimated Salary (Annual, USD) |
|---|---|
| Data Scientist (Entry-Level) | 70,000 - 90,000 |
| Machine Learning Engineer (Mid-Level) | 100,000 - 130,000 |
| Software Developer | 80,000 - 110,000 |
| Cloud Solutions Architect | 120,000 - 150,000 |
| Product Manager | 110,000 - 140,000 |
These figures reflect a competitive stance within the AI and tech consulting sectors, although salaries can vary based on location, experience, and negotiation skills. Compared to startups, Quantiphi offers more structured compensation packages and clearer career progression paths, which appeals to candidates eyeing stability backed by innovation.
Interview Difficulty Analysis
Candidates often describe the Quantiphi interview as challenging but fair. The difficulty lies less in trick questions and more in demonstrating depth and clarity of thought. The multi-stage process can be demanding, especially when balancing technical rigor with behavioral expectations. Some candidates note that technical rounds emphasize practical problem solving over theoretical textbook questions, which can catch unprepared applicants off guard.
Compared to other AI-focused companies, Quantiphi’s interviews score high on applied knowledge, requiring candidates to showcase how they tackle ambiguous problems. This makes preparation crucial but also means that those who understand the company’s focus and client scenarios tend to breeze through.
Preparation Strategy That Works
- Understand the Job Role: Dig into the specific responsibilities and skills listed in the job description. Tailor your study to those areas rather than generic coding practice.
- Practice Problem Solving on Real Platforms: Use HackerRank, LeetCode, or Kaggle for data roles. But simulate timing and communication as if in a live interview.
- Review AI and ML Fundamentals: Brush up on core algorithms, model types, evaluation metrics, and cloud integrations if applying for AI-related roles.
- Mock Interviews: Participate in mock sessions with peers or mentors who can provide honest critiques on both technical and behavioral fronts.
- Prepare Your Stories: Reflect on your past projects and challenges. Be ready to discuss your role, impact, and learnings—Quantiphi interviewers appreciate authentic narratives.
- Stay Current: Be aware of recent industry trends or Quantiphi’s latest projects and news. Demonstrating this awareness can set you apart.
Work Environment and Culture Insights
Quantiphi fosters a culture that thrives on innovation and learning. Candidates often mention a collaborative environment where cross-functional teams work closely. The company encourages experimentation, which means mistakes are seen as opportunities to improve, not failures to be punished.
Work-life balance is reportedly reasonable, although project deadlines can bring bursts of intensity common to consulting engagements. Leadership tends to be accessible, and the emphasis on knowledge sharing creates a healthy ecosystem for those who love growth and challenge.
Career Growth and Learning Opportunities
One thing that stands out at Quantiphi is the structured career progression coupled with continuous learning. Employees get access to cutting-edge tools, certifications, and workshops. Internal mentorship programs and exposure to diverse clients allow individuals to broaden their expertise beyond their immediate technical roles.
The company also supports lateral movements within departments, so someone starting as a data engineer might transition into a data science role after gaining experience. This fluidity is quite attractive in today’s fast-evolving tech landscape.
Real Candidate Experience Patterns
From what candidates share on forums and review sites, Quantiphi interviews tend to leave a lasting impression—sometimes for the right reasons, sometimes less so. Technical rounds can be nerve-wracking, but many appreciate the interviewers’ willingness to guide and clarify questions upon request.
Waiting times between rounds can vary, occasionally extending candidate anxiety, which is an area where candidates hope for improvement. Offers typically come with clear communication on salary and role expectations, which helps reduce post-interview ambiguity.
Overall, candidates who enter the process prepared, with a clear understanding of their own skills and the role, tend to report positive experiences and eventual successful hires.
Comparison With Other Employers
When compared with other AI-focused consultancies such as Mu Sigma, Fractal Analytics, or even larger firms like Accenture’s AI practice, Quantiphi’s recruitment stands out for its technical rigor combined with practical problem-solving emphasis. Unlike some competitors who rely heavily on theoretical assessments, Quantiphi leans toward applied knowledge and client-relevant scenarios.
On the flip side, the company’s size means it might not offer the same level of global mobility or brand recognition as consulting giants. However, for candidates prioritizing hands-on AI work with impactful projects, Quantiphi offers a compelling balance.
| Factor | Quantiphi | Mu Sigma | Accenture AI |
|---|---|---|---|
| Technical Rigor | High | Medium-High | Medium |
| Project Exposure | Industry-specific, hands-on | Data analytics focus | Broad consulting spectrum |
| Career Growth | Structured with lateral moves | Moderate | Extensive but corporate |
| Hiring Process Length | 4-5 weeks | 3-4 weeks | Variable, can be longer |
Expert Advice for Applicants
One piece of advice I often share with candidates aiming for Quantiphi is to approach the interview as a conversation rather than a test. It’s about demonstrating how you think, how you communicate, and how you tackle ambiguity. Don’t rush answers; ask for clarifications if needed. Interviewers respect candidates who engage thoughtfully.
Also, don’t underestimate the HR round—it’s your chance to ensure your values align with the company’s culture. Be honest about your expectations and career goals. It’s a two-way street.
Lastly, context matters. Research Quantiphi’s recent projects or client announcements and weave that knowledge into your answers. It shows genuine interest, not just rehearsed responses.
Frequently Asked Questions
What is the typical duration of Quantiphi’s hiring process?
On average, candidates can expect the complete cycle—from application to offer—to take around 4 to 6 weeks. This varies based on the role and urgency of the hiring need.
Does Quantiphi require a minimum GPA or specific academic qualifications?
While there is no rigid GPA cutoff, strong academic performance in relevant fields like computer science, engineering, or statistics is advantageous. Practical skills and project experience often outweigh numerical grades.
Are there any group discussions or case study rounds?
Unlike many consulting firms, Quantiphi rarely includes group discussions. However, some senior roles may involve case study presentations to assess problem framing and solution communication.
How important is prior industry experience?
It depends on the role. For technical roles, demonstrated technical expertise is paramount. For client-facing or managerial roles, prior industry or consulting experience weighs heavily.
What technologies should I be proficient in before applying?
Commonly expected skills include Python, R, SQL, cloud platforms like AWS or Azure, and familiarity with machine learning frameworks such as TensorFlow or PyTorch. However, specific requirements vary by role.
Final Perspective
Quantiphi’s interview journey is an invitation to showcase not just what you know, but how you think and adapt. The company’s hiring process reflects its broader mission—finding individuals capable of solving complex, real-world problems with AI and data science. It’s rigorous, yes, but also rewarding for those who prepare thoughtfully and embrace the challenge.
For job seekers seriously considering a career at the confluence of AI innovation and client impact, Quantiphi offers a fertile ground. The key is to approach preparation strategically, align your skills with the company’s needs, and bring your authentic self to the table. That’s when the process stops feeling like an interrogation and starts being a meaningful dialogue about your future.
Quantiphi Interview Questions and Answers
Updated 21 Feb 2026Business Analyst Interview Experience
Candidate: Meera Joshi
Experience Level: Mid-level
Applied Via: Recruitment agency
Difficulty:
Final Result: Rejected
Interview Process
3 rounds
Questions Asked
- How do you analyze business requirements?
- Explain a time you improved a process using data.
- What tools do you use for data visualization?
- Behavioral: Describe a situation where you had to manage conflicting stakeholder interests.
Advice
Gain hands-on experience with data analysis tools and be ready to discuss real-world examples of problem-solving.
Full Experience
I was contacted by a recruitment agency and went through three rounds including a technical interview, a case discussion, and an HR round. The technical questions focused on data analysis and business processes. Although I had relevant experience, I felt my answers could have been more structured. I was not selected but received useful feedback.
Product Manager Interview Experience
Candidate: Karan Singh
Experience Level: Mid-level
Applied Via: LinkedIn application
Difficulty:
Final Result:
Interview Process
3 rounds
Questions Asked
- How do you prioritize features in a product roadmap?
- Describe a challenging product launch you managed.
- How do you gather customer feedback effectively?
- Case study: Improve user engagement for a data analytics platform.
- Behavioral: Tell me about a time you led a cross-functional team.
Advice
Prepare for case studies and behavioral questions. Demonstrate clear communication and leadership skills.
Full Experience
I applied via LinkedIn and had three rounds: an initial HR screening, a case study presentation, and a final round with senior management. The case study was challenging but interesting. The interviewers valued my approach to problem-solving and leadership experience. I received the offer shortly after.
Software Engineer Interview Experience
Candidate: Sneha Patel
Experience Level: Entry-level
Applied Via: Campus recruitment
Difficulty:
Final Result:
Interview Process
2 rounds
Questions Asked
- Explain object-oriented programming concepts.
- Write a function to reverse a linked list.
- What are RESTful APIs?
- Behavioral: Why do you want to work at Quantiphi?
Advice
Focus on basic programming concepts and data structures. Also, be ready to explain your projects and motivations clearly.
Full Experience
I was recruited on campus and had two rounds of interviews. The first was a technical test focusing on coding and fundamentals, and the second was an HR round. The interviewers were supportive and encouraged me to ask questions. I got the offer within two weeks.
Machine Learning Engineer Interview Experience
Candidate: Rohit Verma
Experience Level: Senior
Applied Via: Referral
Difficulty: Hard
Final Result: Rejected
Interview Process
4 rounds
Questions Asked
- Explain convolutional neural networks and their applications.
- How do you optimize hyperparameters?
- Design a system for real-time fraud detection.
- Coding challenge: Implement a gradient boosting algorithm.
- Behavioral: Describe leadership experience in a technical project.
Advice
Prepare for system design questions and advanced machine learning topics. Also, practice coding under time constraints and be ready to explain your thought process clearly.
Full Experience
I was referred by a current employee and went through four rounds including a technical phone screen, coding test, system design interview, and a final behavioral round. The questions were challenging, especially the system design and coding parts. Despite my experience, I struggled with some optimization questions and was not selected.
Data Scientist Interview Experience
Candidate: Anita Sharma
Experience Level: Mid-level
Applied Via: Online application via company website
Difficulty:
Final Result:
Interview Process
3 rounds
Questions Asked
- Explain the difference between supervised and unsupervised learning.
- How do you handle missing data in a dataset?
- Describe a machine learning project you have worked on.
- Coding challenge: Implement a decision tree algorithm.
- Behavioral: Describe a time you faced a conflict in a team and how you resolved it.
Advice
Brush up on machine learning fundamentals and practice coding problems related to data structures and algorithms. Also, prepare to discuss your past projects in detail.
Full Experience
I applied through the company website and was invited for a three-round interview. The first round was a technical phone screen focusing on machine learning concepts and coding. The second was a coding challenge followed by a discussion of my previous projects. The final round was with the team lead and included behavioral questions. The process was smooth, and the interviewers were friendly. I received an offer within a week.
Frequently Asked Questions in Quantiphi
Have a question about the hiring process, company policies, or work environment? Ask the community or browse existing questions here.
Common Interview Questions in Quantiphi
Q: A hare and a tortoise have a race along a circle of 100 yards diameter. The tortoise goes in one directionand the hare in the other. The hare starts after the tortoise has covered 1/5 of its distance and that too leisurely.The hare and tortoise meet when the hare has covered only 1/8 of the distance. By what factor should the hareincrease its speed so as to tie the race?
Q: 9 cards are there. You have to arrange them in a 3*3 matrix. Cards are of 4 colors. They are red, yellow, blue and green. Conditions for arrangement: one red card must be in first row or second row. 2 green cards should be in 3rd column. Yellow cards must be in the 3 corners only. Two blue cards must be in the 2nd row. At least one green card in each row.
Q: A rich man died. In his will, he has divided his gold coins among his 5 sons, 5 daughters and a manager. According to his will: First give one coin to manager. 1/5th of the remaining to the elder son.Now give one coin to the manager and 1/5th of the remaining to second son and so on..... After giving coins to 5th son, divided the remaining coins among five daughters equally.All should get full coins. Find the minimum number of coins he has?
Q: There are two balls touching each other circumferencically. The radius of the big ball is 4 times the diameter of the small all. The outer small ball rotates in anticlockwise direction circumferencically over the bigger one at the rate of 16 rev/sec. The bigger wheel also rotates anticlockwise at N rev/sec. What is 'N' for the horizontal line from the centre of small wheel always is horizontal.
Q: There are 3 clans in an island - The Arcs who never lie, the Dons who always lie and the Slons who lie alternately with the truth. Once a tourist meets 2 guides who stress that the other is a Slon. They proceed on a tour and see a sports meet. The first guide says that the prizes have been won in the order Don, Arc, Slon. The other says that, the order is Slon, Don, Arc. (the order need not be exact). To which clan did each of the guides and the players belong? ...
Q: ABCDE are sisters. Each of them gives 4 gifts and each receives 4 gifts No two sisters give the same combination ( e.g. if A gives 4 gifts to B then no other sisters can give four to other one.)Â (i) B gives four to A.(ii) C gives 3 to E. How much did A,B,C,E give to D?
Q: At 6?o a clock ticks 6 times.The time between first and last ticks is 30 seconds.How long does it tick at 12?o clock?2.A hotel has 10 storey. Which floor is above the floor below the floor, below the floor above the floor, below the floor above the fifth.
Q: Every day a cyclist meets a train at a particular crossing .The road is straight before the crossing and both are travelling in the same direction.Cyclist travels with a speed of 10 kmph.One day the cyclist come late by 25 minutes and meets the train 5 km before the crossing.What is the speed of the train?
Q: Tom has three boxes with fruits in his barn: one box with apples, one box with pears, and one box with both apples and pears. The boxes have labels that describe the contents, but none of these labels is on the right box. How can Tom, by taking only one p
Q: Give two dice - one is a standard dice, the other is blank (nothing painted on any of the faces). The problem is to paint the blank dice in such a manner so that when you roll both of them together, the sum of both the faces should lie between 1 and 12. Numbers from 1-12 (both inclusive) equally likely.
Q: Given a collection of points P in the plane , a 1-set is a point in P that can be separated from the rest by a line, .i.e the point lies on one side of the line while the others lie on the other side. The number of 1-sets of P is denoted by n1(P)....
Q: A family X went for a vacation. Unfortunately it rained for 13 days when they were there. But whenever it rained in the mornings, they had clear afternoons and vice versa. In all they enjoyed 11 mornings and 12 afternoons. How many days did they stay there totally?
Q: A Man is sitting in the last coach of train could not find a seat, so he starts walking to the front coach ,he walks for 5 min and reaches front coach. Not finding a seat he walks back to last coach and when he reaches there,train had completed 5 miles. what is the speed of the train ?
Q: Motorboat A leaves shore P as B leaves Q; they move across the lake at a constant speed. They meet first time 600 yards from P. Each returns from the opposite shore without halting, and they meet 200 yards from. How long is the lake?
Q: On a particular day A and B decide that they would either speak the truth or will lie. C asks A whether he is speaking truth or lying? He answers and B listens to what he said. C then asks B what A has said B says "A says that he is a liar"
Q: In a certain year, the number of girls who graduated from City High School was twice the number of boys. If 3/4 of the girls and 5/6 of the boys went to college immediately after graduation, what fraction of the graduates that year went to college immediately after graduation?
Q: Two unemployed young men decided to start a business together. They pooled in their savings, which came to Rs. 2,000. They were both lucky, their business prospered and they were able to increase their capital by 50 per cent every three years. How much did they have in all at the end of eighteen years?
Q: A person starts from his house and walks 2km straight and then takes a right turn and walks for 1km and again takes a right turn and walk for another 1km. now if he is in north - west direction from his house; find out the direction in which he has started from the house?
Q: During a given week a programmer spend 1/4 of his time preparing charts,3/8 of his time for coding,rest of his time for debugging the programs.If he had 48 hrs during the week how many hours did he spend debugging the program
Q: A company contracts to paint 3 houses. Mr.Brown can paint a house in 6 days while Mr.Black would take 8 days and Mr.Blue 12 days. After 8 days Mr.Brown goes on vacation and Mr. Black begins to work for a period of 6 days. How many days will it take Mr.Blu to paint?