FedEx is one of the world’s leading business conglomerates specializing in freight and package transportation, logistics, shipping, and e-commerce. In this article, I shall share my complete assessment and interview experience at FedEx India for the role of Data Analyst.
Background:
FedEx India conducted a national online hiring challenge in October 2022 on the Unstop platform to recruit for their Center of Excellence (CoE) division that supports global stakeholders across diverse domains such as strategic pricing, digital solutions, revenue management, forecasting, and advanced analytics.
Roles Offered:
- Data Analyst
- Marketing Analyst
Eligibility Criteria:
- Final-year students pursuing a full-time 2-year MBA program
- Final-year B.E./B.Tech students across India (all streams)
Online Assessment Details:
The competition structure of the hiring challenge was broadly divided into 4 rounds – 2 Online Aptitude Assessments, 1 Case Study Round, and 1 Technical Interview. Each round of the recruitment process was an elimination round. The aptitude tests for the Data Analyst and Marketing Analyst roles were conducted separately. A total of 1.05 Lakh candidates appeared for the online assessment.
Aptitude Test Round:
- Both rounds of the OA had 20 MCQ questions, to be answered in 30 minutes. There was a 90-second timer provided for each question. Once the time was over for a question, you would be taken to the next question automatically.
- Marks were given for accuracy (number of correct answers) as well as speed (time taken to answer each question).
- Round 1A: The questions were mainly based on Numerical Aptitude (Probability, Time and Work, etc.), Reasoning (Patterns, Series, Permutations), English grammar (Sentence rearrangement, synonyms, etc.), basic SQL commands, and statistical concepts (Mean, Regression, etc.). The difficulty level of this round was easy to moderate.
- Round 1B: Only the Top 10% of the candidates of Round 1A qualified for this round. The pattern was mostly the same, but it had more advanced questions with an extra focus on Machine Learning, DBMS, and SQL. The difficulty level for this round was hard.
Case Study Round:
- A total of 1842 candidates qualified for this stage.
- A PPT presentation template was provided with 4 Problem Statements based on FedEx and the logistics industry.
- The questions were to be answered in 6 slides, supported by data, spreadsheets, references as well as real-world business cases.
- The problem statements focused on topics like the impact of COVID, business and technology trends, market disruption indicators, and mitigation strategies.
- The allowed time for the submission of the Case Study was 10 days.
Technical Interview Details:
It took about 1 month for the results of the Case Study round to be released. The number of candidates qualifying for this round was not revealed. I received a call from the HR of FedEx confirming my qualification for the Technical Interview round, in the first week of December 2022. During the call, I was asked about my skillsets, experience, motivation as well as my interest in working as a Data Analyst. A few hours later, I received an email regarding the interview schedule which was to be held after 2 days.
My Technical Interview lasted for approximately 45 minutes. I faced a panel of 2 technical interviewers who also asked behavioral and non-technical questions.
Technical Questions Asked:
- How would you rate yourself in Python and Microsoft PowerBI?
- What is the difference between a Measure and a Calculated Column in PowerBI?
- How do you typically approach a Data Analysis use case?
- Mention some key points to keep in mind while creating a data visualization.
- What is data pre-processing? Why is it important?
- What is the difference between Heterogeneous and Homogeneous Data?
- When do you use a Line Chart and a Pie Chart?
- What libraries have you worked with in Python?
- Explain the different statistical techniques used in your project.
- What is a data frame? How do you store an existing table in a data frame?
- What is Slicing? With the help of an example, show its usage.
- What is a Dictionary? Can you give a practical example of where Dictionaries are used?
- How do you combine data frames in Python?
- What is Regression? How do you calculate the model accuracy or strength in Linear Regression?
- What is Logistic Regression? Give an application of Logistic Regression.
- Explain the difference between Supervised, Unsupervised, and Reinforced Learning. Mention an algorithm for each type.
- What is a recent Machine Learning trend you are excited about? Can you briefly explain the theory behind it?
- What is a Candidate Key in SQL?
- What is an Alias? How do you create one in SQL?
- What is the meaning of ‘Relational’ in RDBMS?
- Write a SQL program to calculate the Nth Highest Salary from a Table named ‘Employee’
- Tell me about a time you had to use Data Analytics for a personal use case – How did you go about it, what were the variables and parameters you measured, and what challenges did you face?
- Do you have any hands-on experience with Cloud Technology?
Many more cross-questions were asked based on the technical keywords I used in my answers.
Behavioral and Non-Technical Questions Asked:
- Why do you wish to join FedEx?
- Do you know about any major innovation conceived by FedEx in recent years?
- What are some of your achievements apart from the ones mentioned in your resume?
- You have experience in Graphic Designing. How do you think you will incorporate those skills as a Data Analyst?
- Can you briefly tell us about your internship experiences?
- What are your weaknesses – how do you tackle them?
- Tell me about a time you had to convince your team regarding an idea.
- Tell me about a time you encountered difficulty in executing something. How did you resolve it?
Verdict: Selected!
Only 23 students out of the 1.05 Lakh registered candidates were given the job offer at FedEx. Hiring Challenges have always been intimidating for me, so I felt great on receiving the offer.
What worked for me and points to remember:
- When asked to rate yourself on a topic, neither rate yourself too highly nor too low as it will impact the kind of questions the interviewer would ask from that topic. Give yourself an above-average score and mention the reason behind the rating. For example, I rated myself 7 out of 10 in Python and mentioned that I was yet to explore everything the programming language had to offer.
- While answering behavioral questions, always state examples from your personal experience to validate your points.
- Be confident and interactive with the interviewer to express your enthusiasm and positive energy.
- Prepare well on the topics and skills mentioned in your resume as a significant weightage will be given to it by the interviewers.
- Be honest if you have no idea about any topic. Do not lie unless absolutely necessary as it may make things worse.
- Do proper background research about the company before the interview, especially their recent developments and achievements.
- Be aware of the new trends and developments in the industry your job role is based on and research a bit about them.