Explore these career options after completing MSc in Data Science

Data science is one of the most sought-after fields in the 21st century, as it combines the power of mathematics, statistics, computer science, and domain knowledge to extract insights from massive amounts of data. Data science has applications in various industries, such as healthcare, finance, e-commerce, education, social media, and more. Data scientists are in high demand, as they can help organizations make data-driven decisions, optimize processes, enhance customer experience, and create innovative products and services.

In this article, we will explore some of the most popular and lucrative career paths that you can choose from after graduating with an M.Sc in data science in 2024.

Data Analyst

A data analyst is someone who collects, cleans, analyzes, and visualizes data to answer specific business questions or solve problems. Data analysts use various tools and techniques, such as SQL, Python, R, Excel, Tableau, Power BI, etc., to manipulate and present data in a meaningful way.

A data analyst can work in any industry that deals with data, such as banking, retail, education, healthcare, etc. According to PayScale, the average salary of a Data Analyst in 2023 in the US is US$66,638 per year, with a range of US$48,000 to US$91,000 per year.

 Data Engineer

A data engineer is someone who designs, builds, and maintains the data infrastructure and pipelines that enable data collection, storage, processing, and analysis. Data engineers use various technologies, such as Hadoop, Spark, Kafka, AWS, Azure, etc., to create scalable, reliable, and secure data systems that can handle large volumes and varieties of data. Data engineers work closely with data scientists, data analysts, and other data professionals to ensure the availability and quality of data for various purposes. According to Indeed, the average base salary of Data Engineers in 2023 in the US is US$123,307 per year, based on 4.9k salaries reported.

 Data Scientist

A data scientist is someone who applies advanced analytical methods, such as machine learning, deep learning, natural language processing, computer vision, etc., to extract insights and patterns from complex and unstructured data. Data scientists use various tools and frameworks, such as Python, R, TensorFlow, PyTorch, Scikit-learn, etc., to create and deploy data models that can perform tasks such as prediction, classification, clustering, recommendation, sentiment analysis, etc. According to Indeed, the average salary of a data scientist in the US was US$124,276 per year as of December 30, 2023, based on 4.9k salaries reported.

Machine Learning Engineer

A machine learning engineer is someone who develops, tests, and deploys machine learning models and systems that can learn from data and perform tasks autonomously or with minimal human intervention. Machine learning engineers use various tools and frameworks, such as Python, R, TensorFlow, PyTorch, Scikit-learn, etc., to create and optimize machine learning algorithms, such as regression, classification, clustering, reinforcement learning, etc. According to Indeed the average base salary of Machine Learning Engineers in 2023 in the US is US$123,307 per year, based on 4.9k salaries reported.

Business Intelligence Analyst

A business intelligence analyst is someone who uses data to measure and improve the performance and efficiency of a business. Business intelligence analysts use various tools and techniques, such as SQL, Python, R, Excel, Tableau, Power BI, etc., to collect, analyze, and report data related to key business metrics, such as sales, revenue, profit, customer satisfaction, etc. Business intelligence analysts work closely with business stakeholders, such as managers, executives, investors, etc., to provide them with data-driven insights and recommendations that can help them make better business decisions and strategies. According to Indeed, the average salary of a Business Intelligence Analyst in 2023 in the US is US$90,833 per year, based on 7.6k salaries reported.

Data Science Manager

A data science manager is someone who leads and manages a team of data professionals, such as data scientists, data engineers, data analysts, etc. Data science managers are responsible for overseeing the data science projects and initiatives, from planning and scoping to execution and delivery. Data science managers also act as the bridge between the data team and the business stakeholders, ensuring that the data science solutions meet the business goals and expectations. The median salary reported by PayScale was US$146,391, while the average salary reported by Salary.com was US$156,180.

Data Science Consultant

A data science consultant is someone who provides data science expertise and guidance to clients across various industries and domains. Data science consultants help clients identify and solve their data-related problems and challenges, such as data collection, data analysis, data modelling, data visualization, etc. Data science consultants also help clients implement and optimize data science solutions, such as machine learning models, data pipelines, data dashboards, etc. The average salary of a Data Science Consultant in the US in 2023 varied from US$93,062 to US$135,913 per year.

Data Science Educator

A data science educator is someone who teaches and trains others in the field of data science. Data science educators can work as professors, lecturers, instructors, tutors, mentors, etc., in various educational institutions, such as universities, colleges, schools, online platforms, etc. Data science educators are responsible for creating and delivering data science courses and curricula, as well as assessing and evaluating the students' learning outcomes and progress. According to DataCam the average salary of a Data Science Instructor in 2023 was US$117,000, with a range of US$76,000 to US$184,000.