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Table of contents
1.
Introduction📄
2.
About Facebook
3.
About Data Scientist 
4.
Skills Required for the Job
5.
Salary
6.
Preparation Strategy/ Roadmap
6.1.
1️⃣Earn a Data Science Degree
6.2.
2️⃣Sharpen your Relevant Talents
6.2.1.
Programming languages
6.2.2.
Data visualization
6.2.3.
Machine learning
6.2.4.
Big Data
6.2.5.
Cloud Computing 
6.2.6.
Communication
6.3.
3️⃣Get an Entry-level Data Analytics Job
6.4.
4️⃣Prepare for Data Science Interviews
7.
Career Map
8.
Interview Preparation Strategy 
9.
Frequently Asked Questions
9.1.
What’s the work culture like at Facebook?
9.2.
What are the job benefits at Facebook like?
9.3.
How does the Facebook data scientist interview process work?
9.4.
What's the process for getting an internship as a data scientist at Facebook? 
9.5.
What are the challenges of working at Facebook?
10.
Conclusion
Last Updated: Mar 27, 2024

Data Scientist at Facebook

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Speaker
Ashwin Goyal
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18 Jun, 2024 @ 01:30 PM

Introduction📄

We all have heard of Facebook, and most of us have an account on Facebook, but what if you want to join as a Data Scientist at Facebook? Here comes Coding Ninjas with this blog so that you achieve your goals.

This blog will provide info on what needs to be done to become a Data Scientist at Facebook. 

Check out our article on Ways to join as a Data Scientist on Facebook.

So, let's get started.

Data Scientist at facebook

Must Read, Data scientist interview questions

About Facebook

Facebook was founded by Mark zukerburg in 2004. Earlier it was named "The Facebook” 

then after changing it to "Facebook”. Originally limited to Harvard students, membership has expanded to currently include students from other North American colleges as well as, as of 2006, anybody older than 13. As of July 2022, when it was ranked third internationally among the most popular websites, Facebook claimed to have around 3 billion monthly active members. That was the most widely used mobile application in 2010.

About Facebook

Facebook is a website that allows many users to create free Facebook accounts and communicate with their friends, coworkers, and strangers online. It enables users to share many things like images, music, movies, and articles, as well as their own views and opinions, with as many people as they choose.

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About Data Scientist 

The primary goal of a data scientist is to organize and analyze data, sometimes utilizing software created expressly for the job. 

A data scientist's approach to data analysis is determined by their industry and the unique demands of the company or department for which they work. Business executives and department managers must express what they're searching for before a data scientist can uncover significance in organized or unstructured data. As a result, a data scientist must have the sufficient business domain knowledge to transform corporate or departmental goals into data-driven deliverables such as prediction engines, pattern identification analyses, optimization algorithms, and so on.

About Data Scientist

Working as a data scientist may be intellectually stimulating, analytically fulfilling, and place you at the forefront of technological breakthroughs. Data scientists are becoming more prevalent and in demand, as big data becomes more relevant in how corporations make decisions. 

Data scientists utilize technology to extract insights from massive volumes of data. It is a discipline that necessitates knowledge of statistics, quantitative thinking, and computer programming. On top of that, you must be a skilled communicator in order to convey your research findings and explain how they relate to a bigger topic you are attempting to solve.

Skills Required for the Job

Each sector has its unique data profile and set of abilities for Data Scientist to evaluate. Here are some of the most typical types of data analysis that data scientists are likely to do across a number of sectors.

Skills Required

Business: Data analysis of corporate data may help educate judgments on efficiency, inventories, production problems, customer loyalty, and other topics.

E-Commerce

E-Commerce: Data scientists assist e-commerce enterprises in improving customer service, identifying trends, and developing services or products now that websites capture more than just purchase data.

Finance

Finance: Account data, credit and debit transactions, and other financial data are critical to the operation of a corporation. However, security and compliance, especially fraud detection, are important considerations for data scientists in the banking business.

Programming

Programming: The "most fundamental and basic of a data scientist's skill set," programming enhances statistical abilities, allows you to "analyze enormous datasets," and allows you to design your own tools.

Quantitative analysis: Quantitative analysis enhances your capacity to do experimental research, scale your data strategy, and utilize machine learning.

Product intuition: Understanding products can assist you in doing quantitative analysis and better predicting system behavior, establishing metrics, and improving debugging abilities.

Communication: Perhaps the most critical talent in any business, great communication abilities will allow you to "leverage all of the prior skills listed,"

Teamwork

Teamwork: Teamwork is essential for a successful  Data science job, just as communication is. Accordingly, it entails being altruistic, accepting criticism, and sharing information with your team.

Salary

This section will look at the salary of software test engineers at Facebook.

Salary

Salary table

However, the salary figures which are mentioned above are subject to change.

Preparation Strategy/ Roadmap

Generally, being a data scientist necessitates some formal education. Here are some things to think about.

Preparation Strategy/ Roadmap

1️⃣Earn a Data Science Degree

Employers want to see university qualifications to guarantee you have the knowledge to handle a data science job, although it is not always essential. To gain a head start in the industry, consider pursuing a relevant bachelor's degree in data science, statistics, or computer science.

2️⃣Sharpen your Relevant Talents

Consider taking an online course of any website or enrolling in a related bootcamp if you believe you can improve your hard data abilities. Here are some of the abilities you'll wish to possess.

Programming languages

Programming languages

Data scientists may anticipate spending time sorting through, analyzing, and managing massive amounts of data using programming languages. Popular data science programming languages include:

Data visualization

Data visualization

Creating charts and graphs is an important element of being a data scientist. You should be prepared to conduct the task if you are familiar with the following tools:

Machine learning

Machine learning

Using machine learning and deep learning in your data science job means constantly increasing the quality of the data you collect and maybe being able to anticipate the results of future datasets. A machine learning course may teach you the fundamentals.

Big Data

Big Data

Some companies may want to see that you have experience dealing with large data. Hadoop and Apache Spark are two software frameworks used to process large data.

Cloud Computing

Cloud Computing 

Cloud computing allows you to access information and apps online rather than building, managing, and maintaining them on your own hard drive or servers. It's quick, efficient, and safe. Some most popular Cloud Computing Service providers are Microsoft AzureAWS, and Google Cloud Service. 

Communication

Even the most bright data scientists will be unable to make the change if they are unable to effectively convey their results. The ability to communicate ideas and findings vocally and in writing is a highly sought-after skill among data scientists.

3️⃣Get an Entry-level Data Analytics Job

Entry-level Data Analytics Job

Though there are several ways to become a data scientist, a similar entry-level position might be a suitable starting point. Look for jobs using a lot of data, such as Data Analyst, business intelligence analyst, statistician, or data engineer. As your knowledge and talents grow, you may be able to work your way up to being a scientist.

4️⃣Prepare for Data Science Interviews

Data Science Interviews

You may feel prepared to go into data science after a few years of working with data analytics. Prepare responses to anticipated interview questions once you've secured an interview.

Although data scientist employment can be extremely technical, you may be asked both technical and behavioral questions. Prepare for both by stating your response. Having examples from your previous professional or academic experiences on hand will help you look confident and competent to interviewers.

For Interview related preparation, Coding Ninjas can assist you with its great Courses and Study Material:

  1. Aptitude
  2. Interview problems
  3. Preparation Guide
  4. Interview Preparation
  5. Coding Competition

 

Please watch the video for a better understanding of the Data Scientist Roadmap.

Career Map

A career in data science is a wonderful choice if you want a profession that pays well, continually changes, has a lot of room for advancement and allows you to go up the corporate ladder.

Career Map

Data Scientists are compensated well because there is a scarcity of skills. Companies are now more willing to give desired wage packages to those who arrive with the necessary skills and credentials.

And, in order to obtain the necessary abilities and certifications, self-taught learning adventures will not be enough; you will want the advantage of professional training online —- to receive one-hood preparation ranging from syllabus preparation to job interview preparation.

Interview Preparation Strategy 

Let us now create a plan for preparing for your technical rounds and interviews. Check out the Preparation Guide for a thorough guide to joining Facebook. In most cases, one phone interview is followed by 2-3 interview rounds, including technical and HR rounds.

Interview Preparation

  • You should be quite familiar with SQL. The telephone interview will mostly test your knowledge of SQL.
  • Prepare properly for machine learning concepts.
  • You must know how to apply statistical approaches to different types of data.
  • Possess good coding abilities in R or Python.
  • DSA knowledge is also recommended.
  • Know all there is to know about your projects. Create at least 1-2 projects to demonstrate your analytical and statistical abilities.
     

Check out our article on Ways to Join Facebook to find your way to job opportunities at Facebook.

You can also check out Data Analyst vs Data Scientist here.

Frequently Asked Questions

What’s the work culture like at Facebook?

Whether a data science intern or a seasoned machine learning specialist, Facebook takes pride in allowing every data scientist to have a direct and significant influence on the business. According to previous and present workers, the organization favors data scientists who are creative, curious, and proactive, and it has high expectations for all new recruits.

What are the job benefits at Facebook like?

Facebook employees have a plethora of other amenities in addition to high salary packages, flexibility, and campuses throughout the world that include complimentary cafés and restaurants, laundry services, hairdressers, and planned leisure events. Complete coverage health insurance, Every year, employees are given 21 days of paid time off, with an additional 30 days off every five years to rejuvenate. Four months of parental leave and unlimited sick leave.

How does the Facebook data scientist interview process work?

Facebook's interview process for data scientists, like that of many other major tech companies, typically includes phone interviews with recruiters who ask very high-level questions about the applicant's background, the interest of the individual in the company, work experience, and how their goals align with Facebook's mission.

What's the process for getting an internship as a data scientist at Facebook? 

Facebook University—an eight-week paid summer internship for eligible persons from underrepresented backgrounds; a University Grad track for recent college graduates; and a regular twelve-week summer internship—are just a few of the internship tracks available to diverse populations.

What are the challenges of working at Facebook?

There appear to be a limitless number of things to do on Facebook. A lot of success in this field is based on ruthless prioritizing and focusing on the most significant tasks. This entails being acutely aware of project requirements, feeling comfortable challenging stakeholders, and allocating time to alleviate bottlenecks.

Conclusion

Congratulations, as you have gained the basic knowledge about the Data Scientist at Facebook. Since we have discussed the responsibilities, required Skills, Salary, etc., for the Data Scientist at Facebook.

You can also check out Facebook Interview Experience to learn about Facebook’s hiring process.

You can also consider our online coding courses such as the Data Science Course to give your career an edge over others.

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