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14 Data Science Careers to Consider [Skills, Salary, Role]
Data Science

14 Data Science Careers to Consider [Skills, Salary, Role]

13 minute read | December 24, 2022

Ready to launch your career?

The job title “data scientist” is a bit misleading. Because rather than being a single role, data science encompasses a wide range of careers and opportunities. And just as data science roles differ, so too do the qualifications and salary expectations for each position. 

So if you’re looking to jumpstart your career in data science, but aren’t sure which role is right for you, then you’re in the right place. Below, we’ll tell you all about the 14 most promising data science roles and what makes each of them so enticing, so that you can pick which data science career path is right for you.  

Is Data Science a Good Career?

Yes! The mean salary for data scientists exceeds $150,000 a year, and the role of data scientist has been listed as one of the top 3 of the “50 Best Jobs” in the US. Data scientists also tend to report high job satisfaction.

14 Data Science Careers to Pursue

14 Data Science Careers To Pursue

Here are 14 of the best data science jobs to consider:

Data Scientist

A data scientist works with raw data to convert it into meaningful analysis. The analysis helps inform strategic business decisions. Based on the industry, level of expertise, and type of company, a data scientist will engage in data analysis through data scraping and processing. 

Role and Responsibilities

A data scientist’s roles and responsibilities include:

  • Researching and developing statistical and graphical models
  • Implementing reporting dashboards for associated data pipelines
  • Engaging in data visualization to measure the effectiveness of product updates
  • Building data solutions using data cleansing and analysis techniques
  • Testing data movement and performing data and system analysis

Educational Requirements

A data scientist must have completed one of the following:

  • A university degree in computer science, math, engineering, physics, or statistics
  • A data science bootcamp

Other Prerequisites

A data scientist must have:

  • Relevant experience with modern data science methods, classical statistical modeling, and applied mathematics
  • Familiarity with data analysis software like Python and SQL
  • Demonstrated success with processing large data sets


An entry-level salary for data scientists is in the following range:

data science careers, Data Scientist salary

Where to Start

Start your journey as a data scientist with:

Data Engineer

Data engineers develop the appropriate data architecture for the efficient processing of data.

Role and Responsibilities

A data engineer’s role will include:

  • Designing and building data transformation structures
  • Implementing data systems that support core product and business analysis
  • Creating data processing pipelines using Spart, Python, and Hadoop
  • Configuring new data platforms
  • Providing solutions when proposed data structures create issues

Educational Requirements

The following educational requirements are necessary for a data engineer:

  • Bachelor’s or Master’s degree in computer science or a data science bootcamp
  • Certifications like GCP

Other Prerequisites

A data engineer must showcase the following:

  • Experience with Java, Scala, Python, and SQL
  • Working knowledge of ETL (Extraction, Transformation & Loading) data systems
  • Ability to debug SQL queries
  • Excellent project skills


An entry-level data engineer’s salary is in the following range:

data science careers, Data Engineer salary

Where to Start

Take the first step to becoming a data engineer by:

Data Analyst

A data analyst studies data sets and extracts insights that can be used to substantiate strategic business decisions. Data analysts clean their data, then identify patterns using data visualization models.

Role and Responsibilities

Entry-level data analysts do the following:

  • Development and implementation of data analysis processes using statistical techniques
  • Implementation of databases and data collection systems
  • Filtering and cleaning data
  • Identification and interpretation of trends in data sets
  • Creation of dashboards

Educational Requirements

Data analysts have similar educational requirements to data engineers:

  • Bachelor’s or Master’s degree in computer science, or a data science bootcamp

Other Prerequisites

A data analyst is expected to have experience with the following:

  • Tableau, MS Excel
  • Python
  • C#, SQL, and object-oriented programming skills (obtainable through programming certificates)


Here’s the entry-level salary range for a data analyst:

data science careers, Data Analyst salary

Where to Start

You can fast-track your way to becoming a data analyst with:

Data Architect

A data architect creates the blueprint of all the systems and frameworks that a data engineer executes. They also use data modeling to visualize data frameworks.

Role and Responsibilities

A data architect’s responsibilities include:

  • Producing data models based on business requirements
  • Developing and maintaining database systems in collaboration with database administrators
  • Influencing product design by working with support product leaders
  • Setting up scalable research data infrastructure to support data acquisition, data curation, and pipeline development
  • Creating systems for data querying and data archiving

Educational Requirements

A data architect should have:

  • A BA/BS degree in IT or computer science, or have completed a data science bootcamp
  • Certifications like the CDMP

Other Prerequisites

A data architect will stand out if they have:

  • Information systems experience in data management and data architecture
  • Ability to communicate data architecture concepts to non-technical business owners
  • Proficiency in SQL, cloud technologies like Microsoft Azure, AWS, and data visualization tools


A data architect’s annual salary landscape:

data science careers, Data Architect salary

Where to Start

Chart your path as a data architect with:

Machine Learning Engineer

A machine learning engineer works with AI and machine learning systems to build automated workflows for data processing. Their workflows can then be used to develop algorithms that cleanse or analyze data sets to glean patterns.

Role and Responsibilities

A machine learning engineer does the following:

  • Use statistical and econometric methods, predictive models, experimental design methods, and other techniques to help with time series forecasting and causal analysis of data
  • Develop predictive models on large-scale datasets with advanced statistical modeling
  • Implement scalable and efficient modeling algorithms
  • Apply artificial intelligence and deep learning techniques to big-data problems
  • Research client algorithms and tools as a proof-of-concept

Related Read: 8 Best Deep Learning Courses to Grow Your Skillset

Educational Requirements

A machine learning engineer must possess:

  • A Bachelor’s degree in computer science, information systems, statistics, applied math, or have completed a machine learning bootcamp

Other Prerequisites

A machine learning engineer will need:

  • Advanced understanding of deep learning, data mining, and statistical modeling
  • Deep Knowledge of Python, Java, or C
  • Familiarity with statistical modeling tools like R or Matlab
  • Experience with brainstorming and executing machine learning projects


Machine learning engineer salaries are as follows:

data science careers, Machine Learning Engineer salary

Where to Start

You can dip your toes into the machine learning engineering space with:

Data Mining Expert

A data mining expert finds anomalies and patterns in large datasets. With these observations, they develop business solutions or develop business intelligence frameworks.

Role and Responsibilities

A data mining expert must help with:

  • Identifying opportunities for business growth using statistical modeling
  • Studying customer behavior to find trends that will help with business performance
  • Engaging in data analysis and research using specialized software
  • Creating models for data analysis
  • Cleaning datasets for internal and external usage

Educational Requirements

A data mining expert must have:

  • A degree in Computer Science or Mathematics, business administration, data science, or have completed a relevant bootcamp

Other Prerequisites

A data mining expert should exhibit:

  • Strong understanding of programming languages like Python and Java
  • Knowledge of statistics and predictive modeling
  • Familiarity with data analysis tools like SQL and Hadoop


A data mining expert’s salary usually falls in this range:

data science careers, Data Mining Expert salary

Where to Start

Become a data mining expert with:

Business Analyst

Business analysts use data to analyze business growth and solve business problems. The business analyst roles are known to bridge the gap between IT and business productivity and efficiency.

Role and Responsibilities

Business analysts have the following duties:

  • Identify business needs and translate them into actionable goals using data
  • Map business processes and create functional interfaces
  • Define reporting requirements for compliance
  • Troubleshoot data problems
  • Document issues and risks within datasets

Educational Requirements

Business analysts are expected to have:

  • A Bachelor’s degree in IT or computer science
  • Equivalent educational experience through bootcamps and courses

Other Prerequisites

Business analysts must also possess:

  • Familiarity with SQL scripting
  • Validation skills
  • Working knowledge of the software development cycle


A business analyst will earn anywhere between:

data science careers, Business Analyst salary

Where to Start

Give the following resources a spin to start your journey as a business analyst:

Business Intelligence Analyst

A business intelligence analyst processes data for market studies and financial reports. They break down data to help organizations with their marketing efforts and budgetary problems.

Role and Responsibilities

A business intelligence analyst will undertake the following:

  • Development of automated reporting systems
  • Framing of data collection and processing procedures
  • Formulation of business intelligence solutions after analyzing business requirements
  • Maintainance of business user manuals
  • Creation of documentation to streamline business workflows

Educational Requirements

A business intelligence analyst ideally has:

  • Bachelor’s degree in computer science, business administration, and statistics, or an equivalent educational experience through courses and bootcamps

Other Prerequisites

A business intelligence analyst should also:

  • Know how to use data visualization tools like Tableau and Power BI
  • Have familiarity with coding languages
  • Understand financial concepts and possess business knowledge


A business intelligence analyst will earn:

data science careers, Business Intelligence Analyst salary

Where to Start

You can kickstart your business intelligence analyst career by:

Machine Learning Scientist

A machine learning scientist uses data to build complex algorithms that can be used for predictive modeling. They interpret data and solve business problems using machine learning frameworks.

Role and Responsibilities

A machine learning scientist will do the following:

  • Acquire and clean data sets to refine machine learning models
  • Solve operational challenges related to data modeling
  • Develop algorithms to enable intelligent business workflows
  • Work on proof-of-concept studies and research prototypes
  • Evaluate algorithms using tools like PyTorch and Tensorflow

Educational Requirements

A machine learning scientist must fulfill the following:

  • Master’s or Ph.D. in computer science, physics, applied mathematics, or engineering, or have equivalent education in the form of online programs and specializations

Other Prerequisites

Machine learning scientists must show:

  • Proficiency in software prototyping
  • Problem-solving skills to write efficient algorithms
  • An understanding of multiple programming languages


Machine learning scientists earn:

data science careers, Machine Learning Scientist salary

Where to Start

To begin your journey as a machine learning scientist, you need to:

Application Architect

Application architects are responsible for planning and designing software applications. 

Role and Responsibilities

Application architects perform the following roles:

  • Create architectural blueprints for conceptual design and overview of business benefits of an application
  • Establish systems architecture based on business needs
  • Collaborate with software designers for product selection and integration design
  • Develop enterprise-level solutions across platforms
  • Guide user consulting and user stories and support scrum teams

Educational Requirements

Application architects must have:

  • BA/BS degree in computer science, IT, or engineering, or equivalent knowledge in the form of online courses

Other Prerequisites

Application architects will need to show:

  • Experience with design and architectural patterns
  • Understanding of cloud technology
  • Familiarity with Oracle, SQL Server, and other database software


An application architect will earn:

data science careers, Application Architect salary

Where to Start

You can start by:

Database Administrator

A database administrator or database developer maintains database systems, which facilitates the usage of databases by data analysts and data scientists. 

Role and Responsibilities

Database administrators are involved with:

  • Developing and maintaining databases, according to changing business priorities and evolving technological development
  • Focusing on performance tuning of databases across applications
  • Maintaining minimum downtime for database performance
  • Implementing security measures for the protection of databases
  • Resolving database performance issues

Educational Requirements

Database developers should have:

  • A Bachelor of Science degree in computer science
  • Equivalent educational experience through certificates and bootcamps

Other Prerequisites

Database administrators should also know:

  • How cloud databases work
  • The functioning of public cloud offerings
  • Methodologies behind database backup and recovery


A database administrator will earn around:

data science careers, Database Administrator salary

Where to Start

Since you need to immerse yourself in databases, you can try:

Data Modeler

Data modelers are experts who collaborate with data architects and administrators to create databases that are optimized and efficient. They organize data so that internal stakeholders can manage data-backed business processes quickly.

Role and Responsibilities

A data modeler’s responsibilities include:

  • Analyzing source data and creating dashboards for easy digestibility of information
  • Creating prototypes to implement data models
  • Developing standards for data warehouses
  • Working with business and application (and other data science teams) experts to implement data flows and models
  • Collaborating with data engineers to create data visualization and analytic model tools

Educational Requirements

A data modeler must meet the following requirements:

  • Bachelor’s degree in computer science or a related field
  • Equivalent years of experience in the form of hands-on knowledge of data modeling and data software

Other Prerequisites

A data modeler must also show:

  • Experience with cloud-based data warehouse
  • Knowledge of how to perform root cause analysis
  • Advanced SQL knowledge


A data modeler earns:

data science careers, Data Modeler salary

Where to Start

Begin your data modeler journey with:

Data Storyteller

Data storytellers convert data into actionable business insights by using data to build a narrative. They have to translate pure data into a story or case study that will help business owners and internal stakeholders understand the value of the data.

Role and Responsibilities

A data storyteller fulfills the following functions:

  • Conduct deep dive analysis of data to identify compelling use cases
  • Create data visualizations for existing data insights
  • Research customer data insights and convert them into multiple-story mediums
  • Experiment with various storytelling frameworks according to the kind of data at hand
  • Aggregate data points into hierarchies for adequate contextualization

Educational Requirements

A data storyteller needs to have any of these:

  • High School diploma/GED
  • University degree in computer science, engineering, mathematics, or relevant quantitative data fields
  • Social science background
  • Equivalent experience through data storytelling courses

Other Prerequisites

Data storytellers must show:

  • Expertise in designing and building data visualizations using tools
  • Ability to convert technical documentation like whitepapers into use cases
  • Basic understanding of statistical techniques


The average salary for a data storyteller is:

data science careers, Data Storyteller salary

Where to Start

You can explore data storytelling through:

Quantitative Analyst

A quantitative analyst employs numerical assessment models to solve financial questions for businesses. You will find quantitative analyst roles at financial institutions like investment banks and private equity firms.

Role and Responsibilities

A quantitative analyst performs the following responsibilities:

  • Conduct model validations and visualizations
  • Monitor actual exposure versus risk limits
  • Implement risk models
  • Develop reporting packages
  • Assess the performance of different asset classes

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Educational Requirements

A quantitative analyst is expected to have:

  • A Bachelor’s degree in accounting, mathematics, computer science, economics, or finance, or have completed a data analytics bootcamp

Other Prerequisites

To land a quantitative analyst role, you will need:

  • Risk or asset management experience
  • A quantitative background related to investment risk models
  • To know how to interpret technical documentation


A quantitative analyst will earn the following:

data science careers, Quantitative Analyst salary

Where to Start

Start your career as a quantitative analyst with:

Data Science Career FAQs

We’ve got the answers to your most frequently asked questions:

Is Data Science a Stressful Job?

As a data scientist, your job is to spend time analyzing data, and that doesn’t need to be stressful if you have the requisite technical data science skills through bootcamps. Working on your soft skills like communication will also make a data science job easier.

Can You Get Into Data Science Without a Degree?

Yes! You do not need a degree to get into data science. Enrolling in a bootcamp can boost your chances of landing a job in the data science industry. Networking with hiring managers by attending meetups, mixers, and competitions will also help you get your foot into the door. 

Can You Get Into Data Science With No Experience?

Yes, you can get into data science with no experience. Focus on building your skills related to math and programming languages. Enroll in courses for beginners that take you through the fundamentals of data science.

What Skills Do You Need To Land an Entry-Level Data Science Position?

You will need a working understanding of the following to land an entry-level job in data science:

1. Python programming since it is the most common programming language in the data science industry
2. Hadoop platform software because it comes in handy while processing large datasets
3. SQL databases for relational database management
4. Machine learning if you want to stand out amongst your peers to position yourself as someone who understands the role of NLP and automation in the data science field
5. Data visualization so that you can present your data analytic frameworks and information in a digestible visual manner

Does Data Science Require Coding?

Depending on your role, you might have to do some coding. If you are a pure data scientist, you need to know only the basics of coding. A strong understanding of coding will make you a more well-rounded candidate. If you also take on data analyst tasks, coding will become a critical skill to master.

About Akansha Rukhaiyar

Akansha is a freelance writer for SaaS B2B brands, with a parallel interest in writing for mental health services and education websites. She has worked with globally diverse clients and loves to incorporate The Office references in her writing in the most accessible ways