People considering Data Science Job Titles

Take a moment and type in the term ‘Data Science’ into a job search engine. If you do, you will see that thousands of jobs – all with different titles, requirements and expectations – appear. As a person in the data science field, you may be excited at the prospect of mining through the information to find the right fit for you. However, it can always help to know exactly what data science job titles are available and why you may need to consider an option entirely different than what you originally expected. The answers to your questions about the data science field can begin with a better understanding of what types of data science job titles are available in the market today.

Common Data Science Job Titles: Know the Nuances and Define Them Yourself

The most common data science job title with the widest range of expectations you will see if that of “Data Scientist”. This role is generally accepted as a catch all for working through large amounts of data for a company and helping them meet their needs through statistical analyses and research of their data. Each company may have a different and unique reason for a data scientist. Take a moment to consider what motivates you – you may see job titles like “Customer Facing Data Scientist” or “Remote Data Scientist”. Each one of these will offer an additional aspect to the role. Another common data science job title is Software Engineer or Principle Engineer. This type of data science work will generally focus on creations and technology decisions for a company.

The institution you may be interviewing at should be specific on the technical requirements needed and what tools would be available to you to reach milestones. You could work alone in this role or help manage a team on a specific project. While all of these offer some interesting prospects, knowing what you can deliver is as important as knowing what you want. You can learn the nuances of these roles within specific corporations and define how your skills can tailor to the needs. Just as you would comb through data for research, comb through a company’s needs to make sure you both will be satisfied with the end result.

Details on Common Data Science Career Options

  • Data Scientist – spends their time extracting, cleaning and inferring data — usually in large batches. Typical responsibilities include:
    • Predictive Modeling
    • Data Visualization
    • Distributed Computing
    • Reporting and Analysis
  • Data Analyst – collects, processes and conducts statistical data analyses. Spreadsheet tools such as Excel and Tableau are commonly used as well as larger database systems. Typical responsibilities include:
    • Data Mining
    • Data Analysis
    • Data Visualization
    • Communication to Leadership
  • Statistician – collects, analyzes and makes sense of the insights extracted from the data to make qualitative and quantitative business recommendations. Typical responsibilities include:
    • Distributed Computing
    • Cloud-based Analysis and Engagement
    • Data Mining & Machine Learning
    • Communication
  • Database Administrator – oversees and ensures that functions of an organization’s system are running effectively and available to all stakeholders. Typical responsibilities include:
    • Database Management
    • Data Modeling & Design
    • Systems Management
    • ERP & General Business Knowledge
  • Data and Analytics Manager – manages a team of analysts, statisticians and scientists and is responsible for translating the team’s insights and recommendations to internal leadership. Typical responsibilities include:
    • Interpersonal Communication
    • Data Mining
    • Predictive Modeling
    • Leadership & Project Management
  • IT Business Analyst – The IT Business Analyst is the leader who is able to translate big data into simple, meaningful reports that everyone outside the department can understand and act on — commonly known as “translating geek to suit.” Typical responsibilities include:
    • Interpersonal Communication
    • Analyzing, Assessing and Providing Solutions to Complex Business Problems and Systems
    • Needs Consulting
    • IT Support for Regulatory and Compliance Activity
    • Provide Recommendations to Support Business Goals


The shortage of employees possessing deep analytical skills could reach up to 190,000 people by 2018 in the U.S. This will create an employment landscape offering numerous and diverse data science career options for workers who have the ability to apply math, data analysis and modelling techniques to find solutions to business problems. These include high-paying roles that, according to the Bureau of Labor Statistics, will also see tremendous job growth and earning potential in the coming years. For instance:

Data Science Career Options Salaries

As these figures show, a strong background in applied mathematics and data analytics positions workers for career advancement, numerous job opportunities and significant earning potential.

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