How to Start a Career in Data Science: Training, Certifications, and Specialisations

Data science has become an integral part of many industries today as they deal with massive amounts of data that are generated regularly. Data science is the process of using modern tools and techniques to analyze large volumes of data to find unseen patterns, derive meaningful information, and arrive at good business decisions. A decade ago, data science was hailed as “the sexiest job of the 21st century” by the Harvard Business Review, and it has lived up to its reputation ever since.

If you want to start a career in data science, there are certain things you need to do. This article will guide you on how to get started in data science and the pieces of training and certifications you need to be a successful data scientist, data analyst, data engineer, business intelligence analyst, or business analyst.

How to Start a Career in Data Science

1. First, the Basics
   One way to start a career in data science is, to begin with, the basics of programming. Python is a common programming language used for website and software development, automation, data analysis, and visualization.
2. Choose a Field in Data Science and Specialize
   After mastering the basics of programming, the next thing is to select a field and specialize in it. Below are some fields in data science and the required training and certifications:

Data Scientist

A data scientist is responsible for gathering, analyzing, and interpreting data to identify trends, patterns, and insights. To become a data scientist, you must have a minimum of a master’s degree in computer science, mathematics, engineering, or other related fields. Additionally, obtaining industry-recognized certifications such as SAS Certified Data Scientist, Professional Certificate in Data Science (Harvard), Data Science Council of America: Senior Data Scientist, or Microsoft Certified Azure Data Scientist Associate can give you an edge in the job market.

Data Analyst

Data analysts specialize in using algorithms and models to solve specific business issues. To begin a career as a data analyst, you must have at least a bachelor’s degree in statistics or computer science. In addition, you must possess skills in programming languages such as R or SAS, SQL databases, data visualization, and Microsoft Excel. Certifications that are valuable for data analysts include CompTIA Data Analytics Plus Certification, Power BI Data Analyst Associate, IBM Data Analyst Professional Certificate, Microsoft Data Analyst Associate Certificate, or Cloudera Certified Associate Data Analyst.

Data Engineer

Data engineers focus on constructing pipelines for data, gathering data for analytical use, and cleaning data. To become a data engineer, you must have a master’s degree in computer science or statistics. Additionally, you must be proficient in programming languages such as Java, Python, Ruby, Amazon Web Services, and C++, with clear and concise writing and interpersonal communication skills. Certifications that are valuable for data engineers include Google Professional Data Engineer, Cloudera Certified Professional (CCP) Data Engineer, Data Science Council of America (DASCA) Associate Big Data Engineer, or IBM Data Engineering Professional Certificate.

Business Intelligence (BI) Analyst

Business intelligence analysts are responsible for creating visualizations that help businesses understand customer behaviour and market trends. To become a BI analyst, you must have a degree in statistics or any related discipline. Additionally, you must possess skills such as communication and presentation, leadership, problem-solving, and critical thinking. Certifications that are valuable for BI analysts include Microsoft’s Certified Solutions Expert in business intelligence certification, Certified Business Intelligence Professional, TDWI’s Certified Business Intelligence Professional, or SAS Certified Specialist.

Business Analyst

Business analysts are responsible for developing new business processes through the aid of technology. To become a business analyst, you must have a bachelor’s degree in computer science, statistics, or accounting. Additionally, you must possess skills in Microsoft Excel, SQL, negotiation, communication, analytics, and data visualization tools such as Tableau. Certifications that are valuable for business analysts include Academic Business Analysis Certificate (ABAC), Certified Foundation Level Business Analyst, and Certified Advanced Level Business Analyst.

Preparing for Certification Exams

Certifications can help boost your career prospects in data science. However, preparing for certification exams can be quite daunting. Here are some tips to help you prepare effectively:

1. Practice past questions
2. Get guidance from those who have passed the exam
3. Get enough rest
4. Approach the exam with a confident mind

Expected Salary Ranges

One of the perks of a career in data science is the potential for high salaries. According to Glassdoor, here are the average salaries for different data science roles for the current year:

1. Data Scientist – $102,918
2. Data Analyst – $65,909
3. Data Engineer – $94,181
4. Business Intelligence Analyst – $86,763
5. Business Analyst – $85,130

Conclusion

Building a successful career in data science requires a willingness to tackle problems that may seem beyond your current capabilities. Continuously acquiring knowledge and learning new skills is crucial for success in this field. By taking on new challenges and pushing yourself to learn, you can advance your career and become a highly sought-after data scientist. Here are some things to note as you start your journey in data science:

• Keep growing: Learning never ends in data science. Get more certifications, develop more skills, meet people, and build your network. Always try to do a better job every time.
• Be dynamic: Don’t be too one-sided. Be open to trying new things and exploring more career paths. The data science field is continually evolving, and being dynamic will help you stay ahead of the game.