Job positions in data science require extensive experience and a solid understanding of fundamental skills. For those hoping to take the next step in their career, a data science certification can serve as a distinguishing factor from other candidates.
Having a data science certification lets a potential employer know that you have a solid understanding of core data science concepts. It also shows that these skills have been tested and approved by an independent third-party accreditation from a university or national data science organization.
Data science certifications can be incredibly valuable for people who don’t have a higher education background in data science or who want to have specific skills tested. They can also help tech industry professionals get any of these possible jobs.
5 Jobs You Can Get With a Data Science Certification
Average Annual Salary: According to Indeed, the average annual salary for a data scientist is $122,305. Data scientist positions also offer many benefits, including parental leave, stock options, tuition reimbursement, and free food.
Role and Daily Responsibilities: Data scientists will analyze data to understand problems and provide insight for a business. They implement data science processes such as machine learning, statistical modeling, and artificial intelligence to recognize patterns.
Their role is particularly important in the field of data science because it involves many key responsibilities. A degree in mathematics or computer science may be helpful for an entry-level position. However, associate and senior-level positions require specialization to solve more complex problems.
Many data science certifications are specifically suited for getting higher-level data scientist positions. The Data Science Council of America, for instance, offers certifications for all levels of employment, including senior and principal data scientist certifications.
Average Annual Salary: Data engineers receive $131,301 in their average base salary, Indeed reports. Many data engineers also have parental leave, a 401(k) plan, vision, and dental insurance as benefits.
Role and Daily Responsibilities: A data engineer builds and performs maintenance on databases and analytics infrastructure. They are responsible for generating data so that data scientists can then analyze it and move onto the next steps.
Data engineers may require either a master’s degree or doctorate in computer science. However, a data science certification can be extremely helpful, especially if looking to work at a big tech company such as Google or IBM.
Deep Learning Engineer
Average Annual Salary: A deep learning engineer will earn $138,266 annually, according to Indeed. They also may receive benefits, such as visa sponsorship, unlimited time off, stock options, and health and vision insurance.
Role and Daily Responsibilities: Deep learning engineers work on data engineering and AI projects. Deep learning is a subset of machine learning, which allows a machine to learn how to process its own data through artificial neural networks.
Deep learning engineers pertain to a very specialized area of artificial intelligence. A data science certification can help with getting a better understanding of neural network architectures.
Certificates often combine machine learning and deep learning, since they are both needed to understand and work on AI projects. Google has a TensorFlow Developer Certification that tests knowledge on machine learning and deep learning. It also evaluates one’s understanding of TensorFlow which is important to know for specialized engineers.
Machine Learning Engineer
Average Annual Salary: Machine learning engineers earn an average annual salary of $151,183 according to Indeed. Technology companies will also often provide benefits such as unlimited paid time off, visa sponsorship, parental leave, and health and vision insurance.
Role and Daily Responsibilities: Machine learning engineers create AI machines and systems. They implement processes such as machine learning and deep learning so that the machines can make their own predictions and outcomes.
Machine learning engineers typically need a masters’ degree or doctorate in computer engineering or computer science. However, some certification programs can test for a variety of areas that still allow for less experienced individuals to fill the skills gap.
Machine learning engineers require a broader understanding of artificial intelligence than deep learning engineers. Most industry certifications test deep learning and machine learning, which are very important for machine learning engineers.
Average Annual Salary: Algorithm developers have an average base salary of $110,312, Indeed reports. They will also include benefits like an employee stock ownership plan, tuition reimbursement, 401(k) matching, and parental leave.
Role and Daily Responsibilities: Algorithm developers research and test algorithms. Once an efficient algorithm is designed, then it will be used by data scientists who will come up with patterns and trends.
Algorithm developers should have a good understanding of machine learning and design patterns. They should also know how to use programming languages such as C, C++, and Python.
Preparing for a Data Science Certification
Our Data Science training program powered by WOZ prepares individuals for industry-preferred certification exams. The program covers everything from programming languages like SQL, Python, and R, to important concepts like managing big data and learning about machine learning. Participants typically complete the program in as little as eight months.
Since it is a specialized area in the technology sector, a data science certification can help ensure a solid understanding of key concepts. It can also help adult learners who may not have much formal education in data science.
Sophia Acevedo is a journalist based in Southern California. She is a 2020 graduate from California State University, Fullerton, and a proud Daily Titan alum.
This article was published on: 04/26/21 12:05 AM