Intermediate Level Data Science Interview Guide

Greetings 👋

In this article, I cover the typical data science interview process for those with up to 5 years of experience. I’m sharing insights from my personal journey of switching jobs, aiming to help those considering a similar path.

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Currently, I am working as a Data Scientist at Pixis, with a total of over 3 years of experience in this domain. I recently transitioned my job from healthcare to the digital marketing domain. Throughout this journey, I gained a wealth of experience regarding the job switch process, including salary negotiations, among other aspects.

The main purpose of this blog is to share my experiences to guide those looking for a job switch 🧐.

Here, I will walk you through resuming your interview preparation, how and where to find suitable jobs, interview rounds, salary negotiations, and some practical advice you should consider while preparing for a job change.

I aim to present an overall overview of the data science experience, irrespective of companies or job domains.

Contents

• Target Audience
• Resuming Interview Preparation
• Resume Building — Tips
• Finding Suitable Jobs
• Navigating Interview Rounds
• Salary Negotiations and Offer Letter
• Practical Advice for a Smooth Transition

Target Audience 🎯

This article is particularly beneficial for job seekers who are currently employed and looking for a switch. Here, I have covered the end-to-end journey of a job change, from interview preparation to salary negotiations.

Even if you are a fresher or have a senior level of experience, this guide will help you refresh your memory or provide some useful techniques.

Resuming Interview Preparation 🔼

If you are looking for a job change, you should start preparing as early as possible. Typically, it takes around 2 to 3 months to prepare well for interviews.

We can divide the preparation into two parts.

1. General topics
2. Work-related topics

General Topics:

This section covers all the topics that are mandatory to learn before sitting in an interview. You should have a solid understanding and proficiency in the following topics and concepts.

• Programming Langauge — Python
• Coding — Coding in Python
• Frameworks — Pandas, Matplotlib, Numpy, Pytorch(optional)
• Code Editors — Jupyter Notebook, Google Colab
• Descriptive Statistics — Distributions, Charts, etc.
• Probability — Bayes Theorem, Sampling, Probability Distributions etc.
• Inferential Statistics — Central Limit Theorem, Hypothesis Testing, etc.
• Classical Machine Learning Algorithms — Linear Models(Linear Regression, SVM, etc.), Tree-based Algorithms(Decision Trees, Random Forest, Boosting, etc.) and Clustering Algorithms(KMeans, DBSCAN, etc.)
• Deep Learning Algorithms — Neural Networks, MLP, Activation Functions, etc.
• Generic Topics in ML — Bias & Variance, Performance Metrics, etc.
• Generic Topics in DL — Batch Normalization, SGD, Dropout, etc.

To prepare for the above topics, you can search online for authentic resources. If a topic seems complex, consider watching YouTube tutorials. Additionally, I have curated a list of resources; feel free to reach out if needed.

It’s crucial to do hands-on practice for your weak topics, as understanding alone is not sufficient.

How much coding is required?

The coding round for data science is relatively easy and not a mandatory round; some companies do not even ask coding questions. However, one should be well-prepared and can expect questions on string manipulations, arrays, and problems related to greedy algorithms, etc.

Note that if you are preparing for product-based companies, you should have a good understanding of data structures like HashMap, Heap, LinkedList, etc., and their basic implementation in Python.

Work-Related Topics:

It is highly dependent on your day-to-day work. You should have a thorough understanding of the following:

• Tech stack of your work — Language, Deployment, Cloud, etc.
• The end-to-end work cycle of your project — Usecase, Impact, Improvements, etc.
• Data that you deal with — Data Features, Data Engineering, etc.

I suggest writing down all the work you have done so far, even the minor tasks and then try to summarize them in your own words.

Resume Building — Tips 👊

Your resume is your initial representation, so if it’s not well-optimized according to your skills and work, you may get rejected in the early phases of your job application. I have observed many individuals with great skills getting rejected due to poorly constructed resumes.

Resume shortlisting is the starting point of your job journey, and it should be taken seriously.

Here are some important points to note while making it.

• The format should be ATS-friendly. Consider using LaTeX.
• A one-page resume is preferred. Focus on keywords rather than extensive descriptions.
• Avoid using too many colors in your resume — Black and White are generally more effective.
• Your work experience section should detail project use cases, implemented algorithms, and their final impact on both the business and the tech stacks used.
• Personal projects may not be as scrutinized unless they are particularly innovative, so avoid including unnecessary projects as they may consume valuable space without adding significant value.
• Ensure there are no spelling or grammatical errors. Use tools or ask friends to double-check. Avoid fancy or complicated wording; keep the language simple.

Finding Suitable Jobs 🚀

Once your resume is ready, you should start actively applying for jobs that match your experience and skills. Your skills should align with 60% to 70% of the job descriptions.

You can receive interview calls mainly through three methods:

• Referral: Ask friends or connections to refer you to their company if there are openings.
• Job Portals: Websites like Naukri.com, Instahyre, etc.
• Recruiter/TA Direct Calls: Sometimes, the Talent Acquisition team directly contacts you via LinkedIn DM or call if they believe your skills match their requirements.

Here are some tips for using job portals:

• LinkedIn: Update your LinkedIn profile thoroughly, filling in the experience, about, and skills sections. Enable the open-to-work option for recruiters only, and do not make it public unless you urgently need to switch. Activate job alerts based on your work experience and start actively applying. Consider using LinkedIn’s premium free trial once you are ready for interviews.
• Naukri: Create your profile here, update all fields like salary expectations, and try to remain active. It’s not necessary to apply to every opening you see. In the skills section, use only important keywords because recruiters use these skills to match their requirements.
• Instahyre: Create your profile, fill in all the fields, and in the skills section, use only essential keywords. Instahyre only shows jobs that match more than 60% of your skills and work experience, so apply actively here.
• Indeed: I am not very familiar with how it works, as I didn’t receive any calls via this platform.

I primarily used these four job portals, but feel free to explore others. Just ensure you understand how they work to optimize your chances of getting interview calls.

Navigating Interview Rounds 🧭

After applying for a job, the first step is to resume shortlisting, and you will be notified via call or mail about further discussions regarding your application. Typically, you will receive a phone call from the Talent Acquisition team for an initial screening, where they might ask questions about your expected salary, reason for change, job location, and sometimes a brief overview of your work and skills.

If you pass the screening round, the Talent Acquisition team will contact you to schedule further interview rounds. It is always a good idea to inquire about the total number of rounds and the types of questions you can expect in each round.

I have been interviewed by multiple companies, and most of them had 3 to 4 rounds of interviews, including the salary negotiation/HR round. However, this can vary depending on the company’s policy.

Technical Round — 1:

• Duration: 1 hour to 48 hours
• You might be asked to complete some take-home assignments or attend some coding/MCQ tests on platforms like HackerEarth or HackerRank.
• This round is mandatory, and you need to pass the cutoff to advance to the next round.

Technical Round — 2:

• Duration: 45 minutes to 1 hour
• Motive: Measure your breadth of knowledge.
• This round primarily focuses on your basic knowledge and problem-solving skills. You can expect questions from statistics and probability, machine learning concepts, and deep learning topics, mostly related to general concepts like boosting, Central Limit Theorem (CLT), probability distribution, etc.
• The interviewer may also ask you to solve some puzzles/probability puzzles or even code some solutions on the whiteboard in Python.

Technical Round — 3:

• Duration: 1 hour to 1.5 hours
• Motive: Measure your depth of knowledge
• This round can be a bit more challenging and lengthy. You can expect questions about your current and past projects.
• The interviewer will delve deeper into your approach and may ask questions like why you used a particular algorithm, how you evaluated performance, what other methods could have been employed, etc.
• This round also focuses on your contribution and role in the use case you are currently working on.
• The interviewer may also give you some use cases to solve and evaluate your approach.

HR/VP Round:

• Duration: 30 minutes to 45 minutes
• Motive: Check for cultural fit
• This round is usually conducted by the VP, Head of the Department, or HR and is more of a discussion between the candidate and the manager.

Salary Negotiations and Offer Letter 😎

Once you clear all the rounds, the Talent Acquisition team will contact you to discuss salaries and other perks. I suggest conducting some market research about the company beforehand and asking for a salary accordingly.

From a salary perspective, if you are getting a 25% or more hike from your current salary, then it makes sense to switch. You should always ask for a higher salary and be open to negotiation.

Prioritize in-hand salary over total CTC and inquire about other perks like joining bonus, cab facility, food, relocation, etc.

It’s crucial to read the offer letter carefully and ensure you understand all the conditions, notice period, etc., before signing it.

Practical Advice for a Smooth Transition 💁

• Do not wait for the right time to apply — Start actively applying after one month of preparation.
• Do not hesitate to ask for a referral — Referrals are the most effective and easy way to get an interview call. Reach out to people on LinkedIn.
• Salary negotiation is an important skill; do not underestimate it.
• Keywords in your resume or profiles matter significantly, so use them optimally.
• Be prepared and confident in interviews. If you feel lost, take a moment to pause before speaking.
• It’s okay to say “I don’t know” if you are not more than 70% sure about the answer to a question.

In forthcoming articles, I’ll delve deeper into my interview experiences with specific companies, discussing application procedures, interview rounds, and encountered questions in detail.

I hope this guide aids in your job switch journey. Feel free to connect with me on LinkedIn for any queries related to interviews.

Best of luck! ✌️