Data Science Jobs: Salary, Skills, Roles, Qualifications Data science is a quickly growing career field as organizations continue to gather more data about customers. Making a career decision in this field can be difficult as industry demands and job market trends keep on changing. So, how can you choose a rewarding career in this rapidly transforming sector? Here, we have mentioned the most in-demand jobs in data science to help you choose the right one for you. 1. Data Engineer Data engineers develop and maintain ETL pipelines to ensure the accessibility of high-value data for all departments in an organization. They design and support BI (business intelligence) platforms using several techniques, tools, and cloud-based solutions. They also make sure that all big data applications are accessible and work efficiently all the time. Skills and qualifications data engineers need. A bachelor’s or master’s degree in computer science, knowledge of programming languages, data integration, and warehousing. How much data engineers can earn? The average annual salary for a data engineer is $1,25,692, according to Glassdoor. 2. Data Analyst Data analyst remains one of the most in-demand data science jobs and a gateway into data science for beginners. Most companies across all industries are nowadays hiring data analysts to handle data all the way. The main role of a data analyst is to mine data from different sources, clean data to find useful insights and showcase the information to stakeholders via data visualization techniques. Skills and qualifications data analysts need. A bachelor's degree in statistics, computer science, or mathematics, problem-solving and analytical skills, and knowledge of data analysis tools. How much data analysts can earn? The average annual salary for a data analyst is $82,280, according to Glassdoor. 3. Data Scientist A data scientist is one of the most sought-after career options in the world of data science. They use scientific methods, systems, and algorithms to get insights from challenging and large data. They collect, clean, and transform data into easily available forms that other professionals can analyze through several statistical techniques and ML (machine learning) algorithms. Skills and qualifications data scientists need. Master’s degree or Ph. D in statistics, data science, or a related discipline, proficiency in statistical modeling, programming languages, and machine learning. How much data scientists can earn? The average annual salary for a data scientist is $1,57,181, according to Glassdoor.
4. Data Architect Data architects are required to design the data management framework of an organization by evaluating different data sources and combining them into a centralized strategy. They are responsible for analyzing business needs, designing and implementing data models, and ensuring data privacy and security. They also administer the execution of data solutions and monitor performance to ensure the architecture stays updated. Skills and qualifications data architects need. A master’s degree in computer science or a relevant discipline, proficiency in programming languages, database design, data modeling, and data integration technologies. How much data architects can earn? The average annual salary for a data architect is $1,66,257, according to Glassdoor. 5. Machine Learning Engineer A machine learning engineer is a professional behind complex algorithms for speech and image recognition, risk management, consumer insight, and fraud prevention. They develop selfrunning software using data to ensure the automation of predictive models and allow machines to work independently. ML engineers design and run machine learning systems and algorithms. The newly designed models manage the terabytes of data of a company. They often collaborate with stakeholders to identify ML objectives and resolve complicated data problems. Skills and qualifications ML engineers need. An advanced degree in computer science or an associated discipline, expertise in deep learning, artificial intelligence (AI), mathematics, statistical modeling, and programming languages. How much ML engineers can earn? The average annual salary for a machine learning engineer is $1,53,104, according to Glassdoor. 6. Business Intelligence Analyst A business intelligence analyst or BI analyst is important in any company because they use data to help companies make informed decisions. They use the best practices to find the main aspects of improvement and improve the competitive position of an organization. Moreover, they interact with other teams in a company to solve problems. The main role of a business intelligence analyst includes studying current industry trends, examining organizational data to determine business strategy trends, creating useful action strategies, and making reports. Skills and qualifications BI analysts need. A bachelor’s or master’s degree in business intelligence or an associated domain, knowledge of data visualization tools like Power BI and Tableau, skills in data preparation and mining, proficiency in statistical and descriptive analysis, and business modeling. How much BI analysts can earn?
The average annual salary for a business intelligence analyst is $99,864, according to ZipRecruiter. How Can I Get the Highest-Paying Data Science Job? Getting hired by the top companies for a well-paid job in data science requires a combination of essential skills, qualifications, dedication, and practical experience. Here are some tips you can work on to get started with a good career in data science. • • • • •
Pursue a degree in a related field like statistics, computer science, or data science. Develop knowledge in key programming languages like R, Python, etc. Practice data analysis and data visualization using various tools like Tableau, SQL, and Excel. Consider earning data science courses, certifications, or advanced degrees to boost your expertise and credibility. Create a portfolio of real data science projects to demonstrate your skills.
Wrapping Up Data science is a highly rewarding and exciting field with several worthwhile opportunities for aspiring and skilled candidates. These are the top jobs in the field of data science mostly hired by the organization across all industries. Be sure to examine your career goals and then adjust your career decision based on your mindset, skills, and abilities to meet your dream career.
