Data Science Career Opportunities

While the terms data analyst, data scientist, and data engineer broadly describe the various roles data experts can play at a company. There are a number of other jobs which directly relate to these roles or involve the use of data science skills. We'll take a quick look at some job titles you might want to think about when looking for work.

Quantitative Analyst

Quantitative analysts, also known as "quants," use advanced statistical analyses to answer questions and make predictions in the financial and risk industries. Needless to say, most data science programming skills are extremely useful for quantitative analysis, and a strong understanding of statistics is required to succeed in this field. Machine learning models and how they can be used to solve financial problems and predict markets are becoming more widely understood.

Data Warehouse Architect

Basically, this is a sub-field of data engineering for people who want to be in charge of a company's data storage systems. SQL skills are a must for this position, but you'll also need a strong command of a variety of other tech skills, which will vary depending on the employer's tech stack. Although you won't be hired solely for your data science skills, the SQL skills, and data management expertise you'll gain from studying data science will make it a job If you're involved in the company's data engineering department, it's worth considering.

Business Intelligence Analyst

A business analyst is essentially a data analyst who specialises in market and business trends analysis. Although software-based data analysis tools (such as Microsoft Power BI) are sometimes required for this position, many data science skills are also required for business intelligence analyst positions, and Many of these jobs would also necessitate Python or R programming expertise.

Systems Analyst

Systems analysts are frequently tasked with identifying organisational issues and then planning and overseeing the necessary changes or new systems to address those issues. This normally requires programming expertise (though systems analysts aren't often actively involved in the creation of the systems they recommend), as well as data analysis and mathematical skills for detecting troublesome patterns and quantifying what works and doesn't in a company's tech systems.

Operations Analyst

Internal operations are typically examined and streamlined by operations analysts. Although not all operations analyst positions will require data skills, being able to clean, analyse, and visualise data will be critical in determining which company systems are running smoothly and which areas may require improvement in many cases.

Statistician

Before the term "data scientist," data scientists were referred to as "statisticians." The skills required vary widely from job to job, but they all require a thorough understanding of probability and statistics. Programming skills, particularly in a statistics-oriented language like R, are also likely to be useful. A statistician, unlike a data scientist, is unlikely to be expected to know how to build and train machine learning models (although they may need to be familiar with Machine learning models are based on mathematical principles.).

Data Science Internships

Internships are a great option if you're looking for on-the-job training and an entry-level position that often leads to a permanent, full-time position. They aren't for everyone — or even available to everyone — but they do have some benefits that make them worth considering if you're thinking about interning.:

• They are typically paid positions.
• Working data analysts and data scientists are available to work with (and learn from).
• An internship can quickly become a full-time job.
• An internship will easily add valuable experience to your resume if you have no prior data science work experience.