Career Paths in Data Science:
What’s Out There?
The initial phase in any pursuit of employment is recognizing the kinds of occupations you ought to be searching for. In the field of Data Science, this gets confused rapidly. There’s no widespread meaning of “Data Scientist” that each organization concurs on, so various jobs with a similar title may require diverse ranges of abilities. There are plenty of other usually utilized titles that include Data Science work that you probably won’t find in case you’re simply scanning for “Data Scientist” jobs.
- Data Analyst
A Data Analyst is typically considered an “entry-level” position, although not all Data Analysts are junior and salaries can range widely. The primary goal is to look at company or industry data and use it to answer business questions, then communicate those answers to other teams in the company to be acted upon. This process involves accessing the data, typically cleaning it, performing some statistical analysis to answer the relevant business questions, and then visualizing and communicating the results.
You will typically be given business questions to answer rather than asked to find interesting trends on your own, as Data Scientists often are, and you’ll generally be tasked with mining insights from data rather than predicting future results with machine learning.
General skills required:
- Intermediate level programming (Python or R)
- Intermediate level SQL queries
- Data cleaning
- Data visualization
- Probability and statistics
- Communicating complex data analysis clearly and understandably to lay audience
2. Data Engineer
A Data Engineer manages a company’s data infrastructure, requiring a lot less statistical analysis and a lot more software development and programming skill. Primary goal is building data pipelines to get the latest sales, marketing, and revenue data to Data Analysts and Scientists quickly and in a usable format; likely responsible for building and maintaining the infrastructure needed to store and quickly access past data.
General skills required:
- Advanced level programming (typically Python) for working with large datasets and building data pipelines
- Advanced level SQL and Postgres(relational database management system)
3. Business Intelligence Analyst
A Business Intelligence Analyst is essentially a Data Analyst who is focused on analyzing market and business trends. This position sometimes requires familiarity with software-based data analysis tools (like Microsoft Power BI).
General skills required:
- Intermediate level programming (Python or R)
- Intermediate level SQL
- Data cleaning
- Data visualization
- Probability and statistics
- Communicating complex data analysis clearly and understandably to lay audience
4. Data Mining Engineer
A Data Mining Engineer researches, mines data, models relationships, and then reports these findings. From their findings they must find patterns and relationships within large amounts of data in order to make predictions about the future and advise a business about strategy. Furthermore, they typically work with three types of data: transactional, non-operational, and metadata.
General skills required:
- Intermediate level SQL, NoSQL, SAS, and Hadoop
- Advanced level programming (Java, Python, and Perl)
- Intermediate level LINUX
5. Data Warehouse Architect
A Data Warehouse Architect is a specialty within Data Engineering responsible for a company’s data storage systems.
General skills required:
- Advanced level programming (typically Python) for working with large datasets and building data pipelines
- Advanced level SQL and Postgres(relational database management system)
6. Data Scientist
Data Scientists perform their work as Data Analysts, but also build machine learning models to make accurate predictions about the future based on past data. Furthermore, Data Scientists have freedom to pursue their own ideas.
General skills required:
- Expert level programming skills (Python or R)
- Advance level knowledge of supervised/unsupervised machine learning methods
- Advance level understanding of statistics and ability to evaluate statistical models
- Intermediate level Apache Spark
Other Titles in Data Science
- Business Analyst
- Machine Learning Engineer
- Marketing Analyst
- Operations Analyst
- Quantitative Analyst
- Statistician
- Systems Analyst
