How I cracked my Data Science Interview at Paypal?

Landing the Interview

I was working at KPMG when I received an interview call from PayPal. Someone at PayPal had referred me after finding my profile interesting.

They asked if I would be interested in interviewing for a data science role. Within a couple of days, all of the interview rounds were completed.

Round 1: Data Science Projects and Machine Learning

Each round was conducted by different people at PayPal.

One thing that greatly helped me prepare was researching the background of each interviewer right before the round.

By checking their profiles on LinkedIn, I could better understand the types of questions they might ask and tailor my preparation accordingly.

In this round, I walked through one of my previous data science projects from start to finish, making sure to touch on points that could prompt additional questions.

I aimed to proactively answer any questions that might arise about the project. Some examples of potential questions I prepared for were:

• What machine learning algorithms did you leverage and why?
• How did you handle missing or dirty data in this project?
• How well did your models perform and what metrics did you use to evaluate them?
• What techniques did you use when feature engineering?

Round 2: SQL, Python Coding, and Business Case Study

The next round focused on SQL, Python coding, and a business case study. Having used SQL and Python extensively at KPMG, I was comfortably able to complete the hands-on coding.

Some examples that I prepared included aggregating and manipulating tables in SQL, building a machine-learning model in Python, working with APIs, etc.

For the business study, I received some scenario-based questions about how I would approach analytics for a particular domain, my thought process in solving a specific problem, etc.

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Round 3: Behavioural Interview

The final round was a behavioural interview with a senior director.

This round incorporated many technical data and business analytics questions geared towards gauging my ability to think on my feet and communicate effectively.

Some potential questions were:

• How would you go about A/B testing new features or products?
• What experience do you have with natural language processing or recommendation systems?
• Describe how you would analyse user behaviour data to spot trends or anomalies.

Questions I Asked

One technique that helped me in all of the interviews was asking thoughtful questions of my own.

For example, with the HR interviewer, I inquired about what the role entails on a day-to-day basis and the types of problems I could be working on.

In the behavioural interview, I asked what metrics are used to evaluate success for people in this role and what the PayPal analytics team does. I believe this showed my enthusiasm and fit.

Offer and Beyond

After a salary and benefits discussion, I received an offer I was excited to accept.

Preparation and showcasing both my technical abilities and interpersonal skills were important to securing this data science role at a company like PayPal.

Wrapping it up

So that was all about my interview experience.

If you're preparing for data science roles and need guidance, you can connect with senior data scientists on a free strategy call here.

With years of experience in data science, they know what it takes to land these competitive roles.

They'll guide you end-to-end in acing interviews and levelling up your skills.

Also, I have written extensively about how to prepare for Data Science interviews, do check it out.