10 Tips to Land a High-Paying Data Science Job in FAANG Companies

Published on:

16 Jun 2022, 2:30 am

FAANG companies pay a fortune for data science professionals like data scientists, data analysts, etc.

In the past few years, technologies like artificial intelligence, machine learning, and big data have given a new boost to all sectors. From healthcare to manufacturing, every industry is in surviving the digital wave, thanks to the overwhelming data. As more and more industries use innovative big data applications, data professionals of all stripes are in high demand. There are a plethora of data science jobs open for skilled candidates. Despite this, data science jobs command high salaries because there's not enough supply and their skills are in high demand. Especially, FAANG companies pay a fortune for data science professionals like data scientists, data analysts, data engineers, data architects, ML scientists, data storytellers, ML engineers, etc. FAANG refers to the stock of the five most renowned tech companies in the world; these are Facebook, Amazon, Apple, Netflix, and Google. Global recognition, extremely high packages, excellent learning atmosphere, comfortable working hours, and a lot more; this is what attract job seekers to these top-notch companies. Fun fact: Amazon gets nearly 18-20 job applications per minute, Apple has only a 2-3% acceptance rate, and Google receives almost three million job applications per year, so you need to stand beyond the genius bar to land at these brands. Therefore, starting from aspiring data scientists to experts, everybody wants to get into FAANG companies. This article features the top 10 tips to land high-paying data science jobs in FAANG companies.

Start as Early as Possible

"Early Bird Catches the worm". We all have heard this since childhood and there is no better time than now to imply this rule. Some FAANG companies open their internship positions for the next year in the summer nowadays. And they close the opening when it's filled up. You know internships can lead to full-time positions. That is why you should start preparing yourself from today because not being prepared is not an excuse to procrastinate. Nobody is ever prepared completely.

Practice Frequently Asked Questions

Starting early also means preparing yourself for questions that are frequently asked during an interview. Some of the most common questions that you will undoubtedly face are:

Tell something about yourself – Very common but also one of the most crucial questions. Make sure you answer this compellingly and concisely because whatever you say will impact your entire interview. Also, ensure to tailor your answer as per the job description.
Why do you want to work with our company? – This question is to check how well you know about the company. Therefore, do your research and find something unique and appealing which will satisfy the recruiter about your interest.
Why do you want this job? – In this, you must mention the key factors that make you fit for this role and your passion for working with that company.

These are three main questions that are obviously asked along with your strengths and more.

Practice, Practice, and Practice

Make sure you practice interview questions every day. Ask a friend or a professional to help you do a mock interview and ask for feedback. You might find something unexpected you could work on. Practice helps us increase our ability to access information rapidly and automatically. Practice also frees our brains to process more challenging information and problems.

Work On Your Basics

To get selected in the FAANG companies you need to have a solid foundation in your technical concepts. You need to know fundamental technical concepts like:

Data Structure concepts like – linked list, queue, stack, trees, etc.
Core CS subjects like Operating Systems, DBMS, and Computer Networks.
Algorithms like analysis of algorithms, sorting/searching, dynamic programming, etc.
System Design concepts like caching, proxy, load balancing, CAP theorem, and databases.

These are some of the basic concepts which you need to work on to get selected at FAANG companies.

Networking

Make contact with professionals who have a similar background to you and have already made their way into data science. It helps in comprehending the job's challenges and the skills that must be prioritized. Networking is crucial when it comes to establishing oneself in any industry.

Get relevant hands-on experience

Nothing is more important than gaining relevant hands-on experience in data science. It might become complicated to get real-world experience while already working as a data science professional. So, entry-level data science applicants should initially possess experience in various data science projects, volunteer programs, and internships, they can also participate in open-source projects, and can also join coding clubs and hackathons.

Make a systematic action plan

First, identify the activities that are needed in a job search, and then map them out regularly. These plans might often include filling out application forms, practicing data structures, algorithms, and projects, and interview preparations. It will give the applicants a clear mind and vision to proceed forward.

Revision

Revise through various data algorithms, programming concepts, coding questions, math and probability concepts, and other related topics. It is essential to be confident during the interview and not get confused about the questions asked. Hence, good preparation on the previous day will be an efficient start to nailing a data science job interview.

Decide on a target role

For any kind of job search, the target role should be in the direction you will need to follow. Data science is a huge field and without a particular defined target role, you will be left confused. Pursuing the right target role will lead to a better application response rate and interview experience. So, it is important to find the right match between your profile with the companies' idea of the desired candidate.

Learn statistics, machine learning, and different programming languages

Studying statistical programming is essential for data scientists and other data professionals for various reasons. These programming skills allow them to perform statistical analysis and data reconfiguration. Mentioning these skills in your resume will make you sign in front of your competitors and would impress the interviewers.