degree to work in data science

Last Updated on August 28, 2023

Chances are, there’s a data scientist behind every big successful company: Data scientists crunch data and numbers to find ingenious solutions to problems and help their employer rise to the top — or at least compete with their rivals. Sound like an interesting job? Here’s everything you need to know to become and work as a data scientist.

A data scientist is an analytical data expert with technical skills and the ability to solve complex problems. In a way, a data scientist is a mix between a mathematician, computer scientist and trend-spotter — someone who works within the technology and business worlds. And what does that all boil down to? Someone who collects, analyzes and interprets data in order to find ways to help a business improve their operations and get an edge over competitors.

There are many paths to becoming a data scientist — here are a few different options:

Earn a bachelor’s degree — and a master’s degree. According to the Bureau of Labor Statistics, most computer and information research scientists — including data scientists —  “need a master’s degree in computer science or related field, [like] computer engineering.” A master’s program will take you two years, after earning a four-year bachelor’s degree.

Get an entry-level job. You may want to pursue an advanced job, but for now, it’s likely you’ll need to start in an entry-level position, such as a data analyst or junior data scientist. You may want to consider system-specific training or certifications — such as data visualization, business intelligence applications or relational database management — to help get your first job.

Earn a master’s degree or a Ph.D. Data science is a field where your opportunities will be greater with a master’s or doctoral degree, so you may want to consider getting one! You can choose to pursue a master’s in computer science, information technology, math and statistics.

Get a promotion. With a higher degree, more career opportunities have been opened to you, and it may be time to go after a promotion — and earn a higher salary, too.

Also Read: Degree To Work In Data Science, data scientist degree, data scientist job description, best bachelor degree for data science, data scientist career path.

Degree To Work In Data Science

Analytical Skills. According to the Bureau of Labor Statistics, data scientists “must be organized in their thinking and analyze results of their research to formulate conclusions.”

Communication Skills. Data scientists don’t work alone — they work with programmers and managers, and must be able to clearly communicate with them, the Bureau explains.

Critical and Logical Thinking Skills. Because data scientists work on complex problems, critical thinking is a must for success, as is a talent for reasoning and relying on logic.

Math Skills. This probably comes as no surprise, but data scientists “must have knowledge of advanced math and technical topics that are critical in computing,” the Bureau explains.

Ingenuity. When solving complex problems, ingenuity is often needed. Data scientists need to be able to find “innovative ways to solve problems, particularly when their ideas do not initially work as intended,” the Bureau explains.

Hard Skills. Data Scientists must be fluent in a number of different programming languages and software programs. Though there are many different types, Glassdoor research found that Python, R and SQL are three of the most prevalent.

According to Glassdoor data, data scientists can expect to make an average of $117,345 per year. But that number can vary based on where a data scientist works, or their years of experience. For example, a data scientist working at a company with up to 500 employees can expect to earn $112,365 per year, while a data scientist with 15-plus years of experience can earn an average of $141,921 a year, Glassdoor data shows.

Entry requirements

As the name suggests, you will need to be educated to at least degree level and have been awarded at least a 2:1 qualification. However, it is worth mentioning that some schemes require a higher level of education from its applicants.  AXA for example offers a graduate program that requires at least an MSc or PhD.  They also specify that these need to be in data science itself, or another analytic discipline such as physics, maths or computer science.  Others are not quite so exclusive though.  While they do require a degree level qualification, applicants only need an A Level in maths or statistics.  

Data scientists can work in a variety of settings. Those might include:

  • Federal government
  • Computer systems design
  • Research and development
  • Colleges and universities
  • Software companies
  • Car companies
  • Delivery companies
  • Tech companies

Related Careers in Data Science

You may not want to be a data scientist, but there are plenty of other jobs in related fields you may enjoy. Here are a few other options, according to the Bureau of Labor Statistics.

Computer and Information Systems Manager

Average Salary: $142,530

Degrees Required: Bachelor’s degree

Computer Hardware Engineer

Average Salary: $114,600

Degrees Required: Bachelor’s degree

Computer Programmer

Average Salary: $84,280

Degrees Required: Bachelor’s degree

Computer Systems Analyst

Average Salary: $88,740

Degrees Required: Bachelor’s degree

Database Administrator

Average Salary: $90,070

Degrees Required: Bachelor’s degree

Currently, data science is a really popular area to work in. Searches for the term “Data Scientist” have increased by 6 times in 5 years, suggesting that many people want to work in this field. At the moment data science is ranked as the sixth best job on Glassdoor, namely because of its high rate of pay, career opportunities and availability of job openings.

Your interest in data science may have stemmed from another technical discipline, such as software engineering, database development or architecture, actuarial science, any kind of academia, mathematics, biology, astronomy or theoretical physics.

There are several exciting areas of data science…

Artificial Intelligence involves using machines in a way that simulates human intelligence; those capable of exhibiting traits such as reasoning and self-correction. It’s used in business to increase efficiency and enhance performance on a scale that human workers can’t reach alone.

Machine Learning is a practical application of AI that involves teaching computers to learn from data to make the system more intelligent. Businesses are just beginning to make use of Machine Learning to enhance their products. It’s a useful discipline employed in many fields, including game design, recruitment, medicine and customer service.  For the modern data scientist, Machine Learning is now so crucial as datasets have got so large.  It is now too big to simply take it from the database and do the analysis elsewhere.

Data Visualisation is the art of presenting and telling stories with data.

For a Data Scientist, the operative word is ‘scientist’; not engineer, analyst or anything else. Scientists design experiments to further our understanding of reality. This is what distinguishes a Data Scientist from a Data Analyst, Data Engineer, or any other variation.

Industry professionals agree that there is no one straight path that will lead to this most sought after of professions. There are however definite desirables that will set you on the road to greatness.  The section below is designed to allow you an insight into the skills and experience you will need to display in order to pursue a career in this highly competitive arena.

Data science is a hybrid of statistics, computer science and mathematics. As a Data Scientist, you’ll be working at the crossroads between business intelligence and programming. A Data Scientist is defined by their skills using algorithms to make sense of data for business.

Also Read: data analytics degree courses, data scientist salary, bachelor degree in data science, data scientist certification.

data scientist degree

Data scientists are big data wranglers, gathering and analyzing large sets of structured and unstructured data. A data scientist’s role combines computer science, statistics, and mathematics. They analyze, process, and model data then interpret the results to create actionable plans for companies and other organizations.

Data scientists are analytical experts who utilize their skills in both technology and social science to find trends and manage data. They use industry knowledge, contextual understanding, skepticism of existing assumptions – to uncover solutions to business challenges.

A data scientist’s work typically involves making sense of messy, unstructured data, from sources such as smart devices, social media feeds, and emails that don’t neatly fit into a database.

Technical skills are not the only thing that matters, however. Data scientists often exist in business settings and are charged with communicating complex ideas and making data-driven organizational decisions. As a result, it is highly important for them to be effective communicators, leaders and team members as well as high-level analytical thinkers.

Experienced data scientists and data managers are tasked with developing a company’s best practices, from cleaning to processing and storing data. They work cross functionally with other teams throughout their organization, such as marketing, customer success, and operations. They are highly sought after in today’s data and tech heavy economy, and their salaries and job growth clearly reflect that.

Here are six common steps to consider if you’re interested in pursuing a career in data science:

  1. Pursue an undergraduate degree in data science or a closely related field
  2. Learn required skills to become a data scientist
  3. Consider a specialization
  4. Get your first entry-level data scientist job
  5. Review additional data scientist certifications and post-graduate learning
  6. Earn a master’s degree in data science

1. Pursue an undergraduate degree in data science or a closely related field

You will need at least a bachelor’s degree in data science or computer-related field to get your foot in the door as an entry level data scientist, although most data science careers will require a master’s degree. Degrees also add structure, internships, networking and recognized academic qualifications for your résumé. However, if you’ve received a bachelor’s degree in a different field, you may need to focus on developing skills needed for the job through online short courses or bootcamps.

2. Learn the required skills to become a data scientist

  • Programming
  • Machine Learning techniques
  • Data Visualization and Reporting
  • Risk Analysis
  • Statistical analysis and Math
  • Effective Communication
  • Software Engineering Skills
  • Data Mining, Cleaning and Munging
  • Research
  • Big Data Platforms
  • Cloud Tools
  • Data warehousing and structures

3. Consider a specialization

Data scientists may specialize in a particular industry or develop strong skills in areas such as artificial intelligence, machine learning, research, or database management. Specialization is a good way to increase your earning potential and do work that is meaningful to you. 

4. Get your first entry level job as a data scientist

Once you’ve acquired the right skills and/or specialization, you should be ready for your first data science role! It may be useful to create an online portfolio to display a few projects and showcase your accomplishments to potential employers. You also may want to consider a company where there’s room for growth since your first data science job may not have the title data scientist, but could be more of an analytical role. You’ll quickly learn how to work on a team and best practices that will prepare you for more senior positions.

5. Review additional data scientist certifications and post-graduate learning

Here are a few certifications that focus on useful skills:

CAP was created by the Institute for Operations Research and the Management Sciences (INFORMS) and is targeted towards data scientists. During the certification exam, candidates must demonstrate their expertise of the end-to-end analytics process. This includes the framing of business and analytics problems, data and methodology, model building, deployment and life cycle management.

This certification is designed for SAS Enterprise Miner users who perform predictive analytics. Candidates must have a deep, practical understanding of the functionalities for predictive modeling available in SAS Enterprise Miner 14.

6. Earn a master’s degree in data science

Academic qualifications may be more important than you imagine. When it comes to most data science jobs, is a master’s required? It depends on the job and some working data scientists have a bachelor’s or have graduated from a data science bootcamp. According to Burtch Works data from 2019, over 90% of data scientists hold a graduate degree.

data scientist salary

The annual average data of a data scientist is $83,940 per year. Data Scientists at Canada’s Top Companies earn an average of $91,441 per year.

According to Indeed Salaries, the highest paying cities for data scientists are:

  • Regina, SK pays an average salary of $107,716 per year
  • Toronto, ON pays an average salary of $95,892 per year
  • Ottawa, ON pays an average salary of $93,143 per year
  • North York, ON pays an average salary of $87,228 per year
  • Vancouver, BC, pays an average salary of $84,339 per year
  • Victoria, BC, pays an average salary of $83,201 per year
  • Oakville ON pays an average salary of $82,876 per year
  • Calgary, AB pays an average salary of $79,730 per year

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