Before you appear for your technical interview, you must first understand what a data scientist does in top tech companies. Data science is one of the most promising and sought-after career paths you can pursue. FANNG+ companies look for data professionals who can successfully uncover useful intelligence for the organization.
As a data scientist, you should go above and beyond the traditional skills of analyzing massive data volumes, data mining, and programming. You must understand what does a data scientist do to maximize returns at each stage.
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In this article, we will discuss in detail what does a data scientist do, their career path, average salary, and why you should choose data science as your career. Read on to discover what a data warehouse engineer does and other career paths in data science.
Here's what we'll cover:
- Who Is a Data Scientist, and What Does a Data Scientist Do?
- What Skills Should a Data Scientist Have?
- Career Paths in Data Science
- Why Should You Pursue a Career in Data Science?
- Data Scientists vs. Data Analyst: What's the Difference?
- How to Become a Data Scientist at FAANG+ Companies
- How to Prepare for a Data Scientist Interview
Who Is a Data Scientist, and What Does a Data Scientist Do?
You must understand what does a data scientist do before you apply for the role in FAANG+ companies.
A data scientist is a technically skilled, result-oriented individual who is data-driven and adept at building complex quantitative algorithms to sort and synthesize large amounts of information and drive strategy in their organization.
Data scientists have become essential and one of the most valued positions in large companies that have to handle enormous amounts of structured and unstructured data. They should possess a solid background in statistics and programming with a thorough knowledge of data mining, warehousing, and modeling.
FAANG+ and Tier-1 tech companies constantly lookout for data scientists with communicative and leadership skills in addition to data science knowledge for impeccable delivery of tangible results.
If you are preparing for your next data scientist interview, you must know what does a data science engineer do. In your technical interview, you must demonstrate your curiosity, exceptional industry-specific knowledge, and communication skills that portray you as someone who could explain highly technical results to their non-technical counterparts.
What Skills Should a Data Scientist Have?
You must acquire several skills to land a promising data scientist job. As a data scientist, you will have to use the following core skills in your daily work:
- Statistical analysis
- Machine learning
- Computer science to apply the principles of AI, database systems, numerical analysis, human/computer interaction, and software engineering.
- Programming to successfully write code when working in various languages such as Java, R, Python, and SQL.
- Data storytelling
- Math skills include knowledge of advanced math and technical topics crucial in computing.
As a data scientist, you have to communicate statistical ideas to the organizations to help them make sound decisions. There is a need for the following soft skills as well.
- Business intuition
- Analytical and critical thinking
- Inquisitiveness and ingenuity
- Interpersonal and communication skills
- Logical thinking skills
Various Career Paths in Data Science
There are several career paths that you can follow in data science. Here are the most common types of data scientist careers.
- Data Scientist: As a data scientist, you should be skilled at designing data modeling processes to create algorithms and predictive models and perform custom analysis.
- Data Analysts: As a data analyst, you must analyze large data sets and identify trends. You should be able to draw meaningful conclusions when making strategic business decisions.
- Data Engineer: Data engineers are well-versed in cleaning, aggregating, and organizing data from disparate sources and transferring them to data warehouses.
- Data Warehouse Engineer: A data warehouse engineer helps build, manage, and execute data warehouse strategies. They set scopes for projects, choose the appropriate tools, and ensure that all data needs are met.
- Business Intelligence Specialist: They identify trends in data sets and communicate between upper management and the IT department while analyzing data to determine an organization's needs.
- Data Architect: As a data architect, you must be proficient in designing, creating, managing, and deploying an organization's complete data architecture.
Recommended Reading: Machine Learning vs. Data Science — Which Has a Better Future?
Why Should You Pursue a Career in Data Science?
A data science career is emerging as a highly desirable career path with a skyrocketing demand for data scientists in every organization, from startups to Fortune 500s. Data scientist jobs appear in the top 10 best jobs in the US due to their average base salary, active job openings, and employee satisfaction rate. These factors make data science career paths one of the most alluring ones in the US.
Data Scientist Job Growth
According to the United States Bureau of Labor Statistics (BLS), the employment of all computer and information research scientists will rise by 16% by 2028 in the US. The data scientists and mathematical science occupations are expected to grow by 31%, while statisticians by 35% from 2019 to 2029. This rate of increase is much faster and exceeds several other professions.
LinkedIn listed data scientists amongst the most promising jobs in 2021. It also included multiple data-science-related skills in the high-demand skills list. Currently, data scientists are relatively scarce, so it is the right time for you to upskill and enter the field.
What is the Average Salary of a Data Scientist?
The average data scientist salary range is between $105,750 and $180,250 per year. However, total compensation varies considerably depending on location, employee value, years of experience, and core skills. Here is a list of average data scientist salaries in cities across the US, with San Francisco offering the maximum pay.
Data Scientist Salary by Levels
Data scientists’ salary varies based on experience and levels, i.e., there is a pay increase when you move into more senior positions. Let’s take a look at the annual average salary of a data scientist as per job levels:
- Senior Data Scientist: $125,925
- Data Science Manager: $135,401
- Principal Data Scientist: $165,49
Data Scientist Salary at FAANG+ Companies
FAANG+ companies have an extremely high demand for data scientists, and thus they offer one of the highest salaries to data scientists compared to other sectors. Here is a list of what you can expect to get paid on average at top FAANG+ companies annually:
- Facebook data scientist salary: $153,046
- Google data scientist salary: $149,870
- Amazon data scientist salary: $131,021
- Microsoft data scientist salary: $123,328
- Apple data scientist salary: $152,954
Recommended Reading: How to Get Your Dream Job at a FAANG+ Company?
Data Scientists vs. Data Analyst: What's the Difference?
Both data scientists and data analysts work with data, but the main difference lies in what they do with the data. The role of a data scientist is more technical and is often considered to be senior than a data analyst.
Also, learn the difference between Data Engineer vs. Data Scientist.
How to Become a Data Scientist at FAANG+ Companies
There are several paths that you can choose to become a data scientist. Some of the major steps for becoming a data scientist at FAANG+ companies are as follows:
- You must earn a bachelor's degree or a master's degree in a relevant subject. You can uplevel your career by earning a master's degree or a Ph.D. If you are a data scientist with a master's or a doctoral degree in computer science, information technology, math, or statistics, you will have greater opportunities.
- You can begin with an entry-level job such as a data analyst or junior data scientist and advance further. You can also consider undertaking some system-specific training or certifications like data visualization, business intelligence applications, relational database management, and more. When you acquire additional skills, you increase your chances of promotion in the FAANG+ companies.
Learn how to create an impressive data scientist resume here.
How to Prepare for a Data Scientist Interview
Now that you know what does a data scientist do, you must follow a strategic data scientist preparation plan to ace a challenging data scientist interview. Here are some important aspects of data science interview preparation.
A typical Data Scientist interview at FAANG+ companies includes:
- One round of writing SQL queries
- One round based on Python, SQL, and Big Data Frameworks
- Two or three rounds on core Data Engineering concepts
- One behavioral interview round
You must prepare answers to the most anticipated data scientist interview questions. A data scientist position is highly technical, so you must focus on both technical and behavioral questions. You should be prepared with examples from your past academic and professional work experiences.
Recommended Reading: Microsoft Data Science Interview Questions.
FAQS on What Does a Data Scientist Do
Q1. What does a data scientist do at Google?
As a data scientist at Google, you have to carry out all the position's primary responsibilities, which include cleansing, organizing, and manipulating data using pipelines. You will also apply critical principles on the Google Cloud Platform to optimize its services while collaborating with engineers, marketing teams, and product managers to enhance network structure optimization.
Q2. What does a data scientist do at Amazon?
It is vital to understand what does a data scientist do at Amazon before you appear for the technical interview. As a data scientist, you serve as a link between the business and technical sides of Amazon. You should be able to transform and model large-scale data sets. Also, you must provide valuable business insights to stakeholders.
Q3. What does a data scientist do at Facebook?
Facebook data scientists have to suggest data-backed insights to structure the product roadmap and move critical metrics that the product teams track. As a Facebook data scientist, you should know how to build infrastructure that other data engineers use.
Q4. What are the skills needed to become a data scientist?
To become a good data scientist, you should be competent with statistical analysis and computing skills, processing large data sets, mathematics, machine learning, deep learning, data wrangling, data visualization, and programming.
Q5. Is data scientist a high-paying job?
Data scientists earn the most lucrative salaries in the tech industry. On average, a data scientist's salary in the US is $128,789. This compensation includes a base salary of $118,205 and a bonus of $10,584. Senior data scientists also get stock options in their total compensation.
Crack Your Data Science Interview
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