A Primer for Securing Data Science Roles
This article outlines various roles related to data and tech including data analysts, statisticians, and machine learning engineers. Each section provides a brief description, salary, skills, and education, and links to sample projects for you to pursue. Keep in mind that the range of roles and responsibilities depend on the industry and company size and that there is plenty of overlap between, for example, a data analyst and a data engineer. While you do not need to meet every qualification listed, we are here to help you build the fundamental skills!
Data Analyst
Data Analysts apply mathematical and analytical methods to analyze data and help make business decisions. The average base pay for a Data Analyst in the United States is $62,382 (Glassdoor, 2022)
Skills:
- Collect, measure, organize and analyze data
- Technical proficiency in database design development, data models, techniques for data mining, and segmentation
- Knowledge of programming languages like SQL, Oracle, R, MATLAB, and Python
- Proficiency in Excel and data visualization software like Tableau
- Communication and teamwork skills
Statistician
Statisticians apply statistical methods and models to real-world problems. They gather, analyze, and interpret data to help with business decision-making processes. Statisticians made a median salary of $92,270 in 2020. The best-paid 25 percent made $121,800 that year, while the lowest-paid 25 percent made $68,810 (US News).
Skills and Education:
- Many entry-level statistician roles require candidates to hold a master’s degree in statistics or mathematics (more specialized knowledge base compared to a data analyst)
- Statisticians typically have a unique combination of technical, analytical, and leadership skills
Data Scientist
A Data Scientist uses analytical, statistical, and programming skills to collect large data sets and develop data-driven solutions explicitly tailored toward the needs of an organization. While Data Analysts may not need to collect their own data, Data Scientists need more of a technical stack because they are more “end-to-end” through pursuing their own experiments and collecting data. Data Scientists made a median salary of $98,230 in 2020. The best-paid 25 percent made $130,370 that year, while the lowest-paid 25 percent made $71,790 (US News).
Skills and Education:
- Statistics, quantitative reasoning and computer programming skills
- Communication skills so you can report your research findings and explain how they address a larger question you’re trying to answer.
Industry Profile (BLS)
Machine Learning Engineer
Machine Learning Engineers design self-running software to automate predictive models. The average salary for a Machine Learning Engineer is $110,034 per year in Washington, DC (Indeed.com).
Skills and Education:
- Advanced degree in computer science, math, statistics or a related discipline
- Extensive data modeling and data architecture skills
- Programming experience in Python or Java
- Background in machine learning frameworks such as TensorFlow or Keras
- Knowledge of Hadoop or other distributed computing systems
- Experience working in an Agile environment
- Advanced math skills (linear algebra, Bayesian statistics, group theory)
Data Engineer
Data Engineers build pipelines to ensure that data from many sources can be obtained in a form that is clean and conducive to computation. The average salary for a Data Engineer is $93,619 (PayScale).
Skills and Education:
- Bachelor’s degree in computer science, software development, information technology, or a related field
- Learn different programming languages, such as Java and Python, database querying languages, like SQL
- Know relational database management systems and how to design and manage them
Data Architect
A Data Architect formulates the organizational data strategy and defines the data management standards and principles on which the organization operates. They design the “data blueprint” that other data consumers follow and implement. The average salary for a Data Architect is $121,840 (Bureau of Labor Statistics). Typically, Data Architects start in other data roles, such as Data Scientist, Data Analyst, or Data Engineer, and work their way up to becoming Data Architects after years of experience with data modeling, data design, and data management.
Skills and Education:
- Bachelor’s degree in computer science, computer engineering or a related field
- Coursework on data management, programming, big data developments, systems analysis and technology architectures
- Systems development: understand the system development life cycle, project management approaches, and requirements, design, and test techniques
- Data modeling and design: SQL development and database administration
- Established and emerging data technologies: understand established data management and reporting technologies, and have some knowledge of columnar and NoSQL databases, predictive analytics, data visualization, and unstructured data
- Communication and people skills: articulate, persuade, and portray the big data picture to others
Bottom Line
Data Analysts, Statisticians, Data Scientists, Machine Learning Engineers, Data Engineers, Data Architects, etc. are various roles in the data science realm. If any of these job descriptions spark your interest, give the sample projects a try! Many of the skills like Python and database management are transferable to other roles and industries. Investing your time and effort to expand your toolkit now will jumpstart your data science career.
