Data Science Jobs are selling like hotcakes in 2022!
According to the Bureau of Labor Statistics, data science jobs have a growth rate of 18%, making it a great career choice for enterprising professionals.
However, with the job market requirements changing constantly, it might be difficult to put a pin on what is right and what will potentially turn out to be a waste of time. So, we have curated the perfect resources for those enterprising data scientists who are ready to send in their applications!
Here is the summary of this guide to get you started:
- Be active on LinkedIn and other employment websites to be familiar with what skills and requirements are in demand for data scientists
- Send applications for suitable positions depending on the degree you have, be it associates, bachelor's, or master's degree
- While data scientist jobs usually revolve around gathering and analyzing data, you can gather useful skills by scanning job descriptions
- Top-paying companies for data scientists include Oracle, Amazon, Nvidia, Netflix, among others.
You must have a thousand questions running in your head about applying to the right company. We took the liberty of answering some for you:
- How to get a job in data science
- What can you do with a data science degree?
- What are data science job requirements?
- Which are the best places to work as a data scientist?
- How do I get an entry-level data science job?
Here are other data science guides that will be of interest to you:
- What is Data Science?
- Data Science Salary
- Data Science Interview Questions
- Data Science Job Description
- Entry-Level Data Scientist Resume
How To Get a Job in Data Science
If you have what it takes as a data scientist, the actual job-hunting process can be a breeze. Of course, there will be companies that have a different set of expectations from what you can offer but there are other companies that align with yours.
With a potential job market with 11.6 million data science jobs through 2026, the opportunities to get a perfect data science job are endless.
There are a few ways in which you can find data science jobs that fit your requirements:
Network on LinkedIn
One of the requisites to being a modern employee is to have an updated LinkedIn profile at any given time. By updating, we do not only mean adding new information but growing your profile as a data scientist.
If you look close enough, you will find that LinkedIn has plenty of resources to help you gain knowledge and acquaintances. You can join LinkedIn groups that revolve around data science or connect with notable data scientists in the industry.
Be on the lookout for top companies that you want to work for as well, and ensure that you are on top of their recruitment patterns for data scientists.
Stay Updated With Employment Websites
There are other websites like Indeed, Glassdoor, Monster, Google for Jobs, etc. that hosted recruitment calls from companies.
You do not have to set a reminder every week to check all of these websites for data scientist job openings, but check that your notifications are activated to receive updates.
If you do a sweep of these websites, you will also be able to find what skills are in trend and what you need to do to be on par with industry requirements.
Once you have a fair understanding of what you lack, you can take online certifications to build those skills and your data science resume!
What Can You Do With a Data Science Degree?
The scope of data science is so vast that you can find jobs within major industries like Finance, IT, Business Administration, Healthcare, and Environmental Sustainability. However, your job outlook may differ from the kind of degree you possess.
If you have an Associate degree, you will have a higher chance of working as a computer support specialist, statistical assistant, etc.
Source: Analytics India Mag
As a data scientist with a bachelor’s degree, you can pursue job openings like data analysts, data engineers, market research analysts, operation research analysts, etc.
However, with a master’s degree, you can have advanced job roles like data scientist, machine learning engineer, business intelligence analyst, among others.
Since such applicants have experience working along with a comprehensive syllabus, they can reach for complex jobs right away.
Data Science Certifications
If you do not have a degree, fret not for you have a vast repository of data science certifications from various reputed organizations. Start small, and once you have enough knowledge, you can take advanced certifications like:
- IBM Data Science Professional Certificate
- Certified Analytics Professional (CAP)
- Tableau Data Scientist
- HarvardX’s Data Science Professional Certificate
- Amazon AWS Big Data Certification
- SAS Academy for Data Science
- MCSE: Data Management and Analytics
Your data science resume will start engaging with recruiters by manifold if you have such certifications to boast, even without academic credentials. In fact, most companies have lost the obsession with academic requirements, and prefer candidates who have the necessary skills, be it by a degree or by certifications.
Also read: How to Become a Data Scientist
Data Science Job Requirements
There are plenty of job roles that you can search for if you have a fair mix of data scientist skills. You can start as a data analyst and move your way up. One of the complex roles as an advanced Data Scientist would be machine learning and other IT jobs.
That said, here is a job description for a data scientist by Disney:
- Design and develop new predictive models leveraging statistical and machine learning methods to measure and project a user’s engagement with the Disney platforms
- Dig into the drivers of change when interpreting forecasts and build visualizations/interfaces to share results with business stakeholders in an easily digestible, sustainable, and automated manner
- Ensure data is as clean as possible and a reliable source of truth, escalating anomalies and developing workarounds where needed
- Drive innovation by exploring new statistical techniques and brainstorming ways to optimize the existing forecast infrastructure and make processes even better
- Apply Agile principles via participating in standups, sprint planning, writing business requirements documents, and retrospectives
- Collaborate with data engineers, developers, and business analysts
- Design, develop, or improve new user-friendly web applications supporting data science products, contributing to our vision for a “one-stop-shop” forecasting interface
- Develop and deploy testing hypotheses and analyze results, providing the necessary analytical rigor to ensure data quality, consistency, repeatability, and accuracy of insights
- Participate in an “Open Source” learning environment where sharing, documenting, teaching, and collaborating with others is the culture
Here is a requirements section of a job description for a data scientist for Google:
Minimum Qualifications:
- Bachelor's degree or equivalent practical experience.
- 3 years of experience with statistical packages(R, SAS, Stata, MATLAB).
- Experience in articulating product questions, extracting data from datasets (SQL), and arriving at answers by using statistics.
Preferred Qualifications:
- Bachelor's or Master's degree in a quantitative field such as; Mathematics, Computer Science, Engineering, Statistics, Data Sciences.
- Experience in extracting large sets of data, scripting with SQL, and design of ETL flows.
- Experience in an interdisciplinary/cross-functional field.
- Interest and aptitude in data, metrics, analysis, and trends and applied knowledge of statistics, measurement, and program evaluation.
- Ability to translate analysis results into business recommendations, and excellent written and verbal communication skills.
- Remarkable problem-solving skills and business judgment.
Find out more: Data Scientist Job Description
Best Places to Work as a Data Scientist
Depending on what your interests are, you can work for hospitals, finance companies, media companies, technology companies, and even the government!
However, working for a well-known company is bound to shine on your resume if your goal is to progress along your career path. Once you have gained considerable experience and skills in the field, your focus can move from working for big companies with mediocre pay to negotiating your skills for a suitable yet higher pay.
Some of the top-paying companies for data scientists are:
| Company | Salary |
|---|---|
| Oracle | $124,333 |
| $162,931 | |
| Lyft | $157,798 |
| Uber | $146,032 |
| Nvidia | $197,500 |
| Netflix | $173,503 |
| Airbnb | $197,800 |
| Cloudera | $143,000 |
Be on the constant lookout for job openings from these companies, and make sure that your resume is application-ready to speed up the process!
Such companies have a rigorous recruiting process without spending too much time. With software like the Applicant Tracking System, only the deserving data scientists will be reviewed by a recruiter.
So even if you do have the skills, it can be difficult to rank high among the rest of the candidates if your resume does not pass the ATS.
Also read: Data Scientist Salary
Data Science Positions
Once you get into the field of data science, there is only moving up! With an incredible rise in opportunities, you have plenty of scope to build your knowledge and expertise as a data scientist.
Source: PayScale
For freshers, the immediate opportunities available would be data analysts or junior data scientists. With 2-4 years of experience, you may be able to get a data scientist job and further your career with a senior data scientist role.
If you venture into the IT space, you can get opportunities in Machine Learning or Artificial Intelligence.
Data Science Industries
It is not just businesses that need data scientists. Since their responsibilities involve deriving meaningful insights from data, a lot of industries make good use out of them. You can choose to work in any of these industries, such as:
Banking and Insurance
Data scientists, in this scenario, derive crucial metrics such as customer behavior, consumer insights, claims management, etc.
They monitor financial market activity from consumers and help the industry serve their financial needs better.
Media and Communications
The media industry is ever-expanding as more consumers get involved. With the help of data scientists, media companies find it much easier to deliver customers' requests intuitively.
They do this through detailed sentiment analysis and tracking user interests which helps customers find shows they like based on their individual interests.
Healthcare
One of the most important industries, data scientists aid in faster identification and efficient analysis of heathcare information. They facilitate effective storage of patient data, which contributes greatly to the industry.
Education
By analyzing requirements from students of all walks of life, AI combined with analytics helps in revolutionizing modern-day learning by integrating innovative teaching methodologies.
Manufacturing
Data scientist jobs in this sector go toward analyzing huge chunks of data from manufacturing industry and thereby increasing productivity and profit margins.
Retail and CPG
The involvement of data scientists in this industry has contributed to an improved shopping experience. Not only that, analyzed data has helped reduced frauds and assisted in timely analysis of inventory.
The boom in the retail industry benefited off of data scientist jobs and has helped maximize growth.
Energy and Utilities
With scientific and well-grounded analytics, data scientists have facilitated deeper understanding of energy consumption. The enhanced knowledge has contributed to better consumption of utilities and efficient use of energy.
Data Science Careers: What Should be Your Next Stop?
If you want to build your knowledge or progress into other careers, you are at the right place. A good foundation of data science basics opens up a lot of career options, all of them rewarding. Here are some of them:
Data Analyst
By interpreting and manipulating big datasets, data analysts gather meaningful insights and conclusions to facilitate better decision-making to bolster business growth.
You can work in conjunction with company stakeholders to analyze valuable data and save plenty of resources just by gleaning appropriate results. Data analysts are in great demand at the moment, the U.S. Bureau of Labor suggesting that it is growing at a faster than average rate.
Machine Learning Engineer
Businesses have begun to invest in machine learning engineers at a greater rate. Jobs in the field have increased by 75% over the last 4 years, and it is due to their skill of developing AI tools to solve business roadblocks and automate predictive models.
ML engineers provide innovative solutions with their extensive knowledge in programming, data manipulation, and software engineering.
Data Engineer
With deeper knowledge in software engineering, data engineers prepare data for use by data scientists or data analysts. They structure and process data for analytical purposes that facilitate better decision-making.
Data engineering jobs are predicted to grow 50% year-over-year due to their incredibly advantageous work to businesses. They convert raw unfiltered data into pipelines and structures that can be manipulated.
Business Intelligence Developer
With the time-sensitive nature of business initiatives, companies demand quicker effective solutions with minimal waste of resources. Business intelligence developers perform the task of gathering critical information to design useful business strategies that contribute to business growth.
The job role requires a great degree of acquaintance with current technology and BI tools for maintaining BI interfaces.
Statistician
With a projected growth rate of 30% from 2018 to 2028, statisticians orchestrate data to make better business decisions. From strategizing, collecting data, and using models, statisticians glean meaningful insights.
They use applied statistics and mathematical models to communicate results to stakeholders and pave way for business growth with maximum optimization of company resources
Find out more: Data Science Career
Key Takeaways
The field of data science has seen incredible growth over the past few years and is set to grow further in upcoming years. In such a volatile industry, you need to start your data scientist career strong with the right opportunities.
Here is what you need to know before you apply for data science jobs:
- Stay updated with employment websites like Indeed, Glassdoor, PayScale, etc. to keep track of companies that you want to work for
- Be active on LinkedIn and network with other users to build your knowledge base and connections
- Gain certifications from reputable organizations and gain proficiency in skills that are in-demand
- Be on the lookout for popular companies and apply for suitable positions to fastrack your career in the best way possible
Keep in mind that with such a vast job market, there will be companies searching for candidates with your skill set, so keep searching!
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