Data Science Career Paths

In the modern digital age, data is now the currency of business, and data science career paths are in-demand. In this post, we’ve collected standard job titles, their typical requirements, average salary, and the required skillset to hold them.

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In the modern digital age, data is now the currency of business, and data science career paths are proving to be both in-demand and numerous.

More and more, the rise of big data means big opportunities for those possessing specific data science skill sets. It pays to know how to collect, clean, sort, and analyze data in a way that is valuable and provides actionable insights. 

In this post, we’ve collected some standard job titles, their typical requirements, average salary, and the required skillset to hold them. If you’re interested in data science career paths, here’s what to look for.

What is Data Science?

In simple terms, data science is using and preparing data for analysis. It is a data scientist’s job to clean and analyze it to provide digestible and actionable insights to decision-makers and business leaders.

There is a growing need for data scientists and analysts globally to help navigate a digital-first and data-driven global market. Data science is used in just about every corner of the economy – from political forecasts and predicting sports outcomes to forecasting media trends and warning of business slowdowns. Data scientists turn mountains of captured data into neatly packaged, connected dots that detect trends, make predictions, and provide insights into an organization’s goals.

Why pursue a career in Data Science?

The current marketplace combines a high demand for data scientists with a shortage of qualified applicants, making it the perfect opportunity for those interested in entering the field.

Research shows there was a shortage of 250,000 data science professionals in 2020. In addition, 35% of organizations surveyed said they anticipated difficulty finding skilled candidates for data science roles. (1) What’s more, the U.S. Bureau of Labor Statistics reports that the demand for data science skills will drive a 27.9 percent rise in employment in the field through 2026. (2) 

For those with the needed skill sets, companies are paying top dollar, especially for candidates familiar with emerging technologies such as cloud computing, A.I., and machine learning. (3)

Entry-Level Roles

Data Analyst

Average salary: $93,262 USD*

Typical job requirements: A Data Analyst collects and stores data on sales numbers, market research, logistics, linguistics, or other behaviors. They ensure the quality and accuracy of data, then process, design, and present it to help stakeholders make better decisions.

Typical skillset required: Java, Python, SQL, R, Scala

Junior Data Scientist

Average salary: $115,586 USD*

Typical job requirements: Junior Data Scientistsinterpret and manage data and solve complex problems with the help of various data software. A typical job description for a Junior Data Scientist would include things such as having an extreme passion for data science and data analysis, being able to conduct data mining, and working in teams.

Typical skillset required: Java, Python, SQL, R, Scala 

Data Engineer

Average salary: $116,206 USD*

Typical job requirements: Data Engineers are responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise. This IT role requires a significant set of technical skills, including a deep knowledge of SQL database design and multiple programming languages.

Typical skillset required: SQL, Python, R, and Scala

Database Administrator

Average salary: $101,097 USD*

Typical job requirements: Database Administrators are responsible for the management and maintenance of company databases. Database Administrators’ duties include maintaining adherence to a data management policy and ensuring that company databases are functional and backed up in the event of memory loss.

Typical skillset required: SQL, PHP, Python, R, C#

Mid-Level Roles

Data Mining Engineer

Average salary: $114,682 USD*

Typical job requirements: A Data Mining Engineer is an advocate for both the database system and its manager. They advise company executives on the best equipment and software to meet the company’s needs and look for opportunities to improve the system and increase its relevance to company goals.

Typical skillset required: Python, Java, R, MapReduce

Data Scientist

Average salary: $118,537 USD* 

Typical job requirements: Data Scientists work closely with business stakeholders. They work to understand their goals and determine how data can be used to achieve those goals. They design data modeling processes and create algorithms and predictive models to analyze data. Combining computer science, modeling, statistics, analytics, and math skills data scientists help organizations make objective, data-driven decisions.

Typical skillset required: Python, SQL, Java, R, Scala

Senior Level Roles

Data Architect

Average salary: $133,823 USD* 

Typical job requirements: Data Architects build and maintain a company’s database by identifying structural and installation solutions. They work with database administrators and analysts to secure easy access to company data. Duties include creating database solutions, evaluating requirements, and preparing design reports.

Typical skillset required: Python, Java, C, C++

Machine Learning Engineer

Average salary: $122,844 USD*

Typical job requirements: Machine Learning Engineers develop self-running AI software. This software automates predictive models for recommended searches, virtual assistants, translation apps, chatbots, and driverless cars. They design machine learning systems, apply algorithms to generate accurate predictions, and resolve data set problems.

Typical skillset required: Python, Java, R, Julia, LISP 

Breaking Into The Field

If you want to break into any of these data science career paths, it’s critical to learn the required programming languages for your target title. 

This can be achieved in several methods – including with university classes or self-teaching – but by far the most time-conscious and cost-effective way is by enrolling in a technical training course that will get you to your goals faster. 

These courses are completed in months, not years, cost a fraction of traditional university tuition, and provide practical training to prepare graduates to jump headfirst into their first position. Short-term, intensive courses teach you up-to-date skills that won’t be obsolete when you graduate. 

Check out all the programming languages and skills Flatiron School will teach you. 

Ready to take the next step? Start with a Free Data Science Prep Work, or check out the Data Science Course Syllabus that will set you up for success with the skills to launch you into a fulfilling and lucrative career.

* Salaries cited current as of June 2022 

Sources:

  1. https://quanthub.com/data-scientist-shortage-2020/
  2. https://www.bls.gov/
  3. https://fortune.com/education/business/articles/2022/02/24/a-hot-market-for-data-scientists-means-starting-salaries-of-125k-and-up-this-year/#:~:text=Data%20scientists%20made%20a%20median,%24152%2C500%20median%20salary%20in%202019
  4. https://www.glassdoor.com/index.htm

Disclaimer: The information in this blog is current as of 28 June 2022. For updated information visit https://flatironschool.com/

Posted by Anna Johnson  /  June 28, 2022