The Data Science Career Path: Building Skills to Future-Proof Your Career

The surge in data-driven decision-making has turned data science into a booming job space. The U.S. Bureau of Labor Statistics projects 34 percent growth in the profession from 2024 to 2034, a rate that ranks it among the nation’s fastest-growing occupations. 

From healthcare and finance to marketing and public policy, organizations increasingly rely on data to operate and plan. Consequently, demand is growing for professionals who can analyze data and translate it into actionable insights. Those with the skills to navigate the evolving data landscape should be well-positioned for strong career prospects.

This article offers a roadmap for the data science career path, highlighting the foundational and advanced skills required to thrive in the field. From statistical modeling and artificial intelligence to ethics and communication, this article examines the capabilities that set data professionals apart in an increasingly data-driven world. It also explores how you can develop these skills with an online graduate degree from Merrimack College in data science, computer science, or information technology.

Data Science Career Paths

Flexibility and relevance to nearly every field make the data science career path a compelling option. Employers in healthcare, finance, technology, insurance, retail and government are actively hiring data professionals to solve problems ranging from fraud detection to public health forecasting. Opportunities abound throughout the public and private sectors.

Data science attracts individuals from diverse academic and professional backgrounds. While many arrive with STEM training, it is not necessary; Merrimack College does not require a STEM background for its graduate programs. 

Data science drives the growing field of business analytics, which leverages data to formulate business forecasts and drive decision-making. This interdisciplinary nature makes data science a dynamic option for those looking to apply technical skills to real-world challenges.

Data science professionals often start their careers in entry-level data science jobs such as data analyst or junior data scientist, where they focus on tasks like data cleaning, visualization and basic modeling. These positions are common entry points for those who have recently earned a relevant bachelor’s degree. As AI eliminates many of the positions traditionally taken by recent undergraduates, advanced training—such as a master’s degree—will become a more important factor in career development.

With experience and further credentials, data scientists move into more advanced roles (e.g., machine learning engineer, data engineer or senior data scientist) that involve building predictive models, managing large datasets and contributing to strategic decisions. At the highest levels, professionals may step into leadership roles like chief data officer or director of analytics, guiding data strategy across an organization.

Essential Data Science Skills for Career Growth

A successful data science career is built on a blend of technical expertise and the professional skills needed to work effectively in both business and technical settings. Core technical skills include:

• Proficiency in programming languages such as Python, R, and SQL, which are essential for data manipulation, analysis, and automation
• A strong foundation in statistics and applied mathematics, which supports accurate modeling and interpretation
• Knowledge of machine learning and AI fundamentals, which enables professionals to develop predictive tools and intelligent systems
• Data visualization and storytelling, which data scientists utilize to communicate complex findings clearly and persuasively to stakeholders

Equally critical are problem-solving, communication and collaboration skills. Data professionals typically need to work across teams, understand business needs and translate analytical insights into strategic decisions. Professional communication skills are critical in this field.

Merrimack College’s Master of Science in Data Science program is designed to build these essential competencies. Courses such as SQL and Python Programming, AI for Text and Images, and Machine Learning and Artificial Intelligence provide hands-on experience with industry tools and real-world applications. The program is adding courses in business storytelling to promote presentation and persuasion skills. Through this integrated curriculum, students develop the skills needed to thrive in diverse environments, from tech firms and healthcare systems to financial institutions and government agencies.

Data Science Jobs and Career Opportunities

The data science field encompasses a range of specialized roles, each with distinct responsibilities and required skills. Below are brief summaries of some of the most common positions along the data science career path. Reported salaries reflect Indeed.com data at the time of publication.

Data Engineer

Data engineers design and build the systems and architecture that enable organizations to collect, store and process large volumes of data efficiently. Their work supports data science by ensuring reliable, scalable access to clean and organized data for analysis and modeling. Data engineers typically earn an average base salary of about $132,000.

Data Scientist

Data scientists analyze complex datasets to uncover patterns and build predictive models that inform strategic decisions. They combine skills in statistics, programming and machine learning to solve real-world problems across industries. Data scientists earn an average base salary of around $129,000.

Machine Learning Engineer

Machine learning engineers develop algorithms and deploy models that enable systems to learn from data and make predictions or decisions with minimal human intervention. This role builds on core data science principles, such as statistical analysis and programming, and extends them into software engineering and scalable model deployment. Data engineers typically earn an average base salary of about $132,000.

Statistician

Statisticians design experiments and analyze data to support decision-making in fields such as healthcare, government and business. Their work incorporates core data science skills, including statistical modeling, data visualization and programming in tools like R or Python. Statisticians earn an average base salary of approximately $95,000.

The Future of Data Science Jobs

The future of data science is being shaped by rapid advances in technology and growing expectations for ethical, scalable data use. Trends redefining how organizations manage and apply data include:

• AI-driven analytics, which automate complex analysis and enable faster, more accurate insights across business functions
• Cloud-based platforms, which allow scalable storage, computing, and collaboration while reducing infrastructure limitations
• Data mesh architecture, which decentralizes data ownership across teams to improve agility, accessibility and domain-specific insights
• Explainable and ethical AI, which ensures transparency in model decisions and aligns algorithmic outcomes with organizational values and societal norms
• The integration of privacy and governance frameworks, which embeds compliance, data quality and responsible use directly into data workflows 
• Streaming AI, which enables real-time data processing and decision-making for applications like fraud detection, personalization and predictive maintenance

As a result, new roles are emerging, including AI governance specialists and applied data engineers. These positions demand professionals who can adapt to evolving tools, regulations and business needs.

While automation and generative AI may streamline certain routine tasks such as basic data cleaning or dashboard generation, the need for skilled practitioners who can interpret results, build responsible models and align analytics with strategic goals remains strong. Roles that rely heavily on human judgment and cross-functional collaboration—like data scientists, machine learning engineers and data ethicists—are likely to endure and evolve rather than disappear. In this shifting landscape, a strong foundation in data science ensures professionals are not only relevant but also equipped to lead in a data-driven future.

How Computer Science and IT Connect to the Data Science Career Path

Data science, computer science and information technology are closely linked disciplines. Each contributes essential skills to the modern data landscape:

• Computer science provides the algorithmic thinking, programming skills, software engineering and systems design that underpin data pipelines and machine learning models. As AI tools are increasingly incorporated into software projects, software engineers will need proficiency in assessing and using them.
• Information technology focuses on managing data infrastructure and ensuring system security, both essential for deploying scalable, reliable analytics solutions. Here, too, AI-driven solutions will gain prominence going forward.

Many professionals begin their data science careers through computer science or IT programs, where they gain foundational knowledge in programming, databases and applied analytics. Merrimack College offers multiple entry points tailored to different student backgrounds and goals: the Master of Science in Computer Science (MSCS) for those interested in software and systems, the Master of Science in Information Technology (MSIT) for infrastructure and enterprise tech pathways, and the Master of Science in Data Science (MSDS) for those focused on analytics, modeling and machine learning. The school also offers graduate certificates in AI engineering, applied AI, cybersecurity, and data science foundations.

Choosing the right program depends on where you’re starting and where you want to go—but all three degrees build the technical expertise needed for a future in data science.

Graduate Education and Long-Term Career Success

An advanced degree can significantly accelerate a career in data science by equipping professionals with the depth and versatility employers increasingly expect. Many organizations now seek candidates with graduate-level credentials to fill roles that demand expertise in machine learning, predictive modeling and data-driven strategy. Through programs like Merrimack College’s online master’s degrees, students gain the kind of hands-on experience employers value.

Graduate education offers multiple benefits beyond technical education. They include:

• Access to faculty mentorship and networking
• Career support services
• Higher earning potential and promotion opportunities
• Meeting employer expectations for advanced credentials

Merrimack’s programs are designed with working professionals in mind. They offer affordability, flexible scheduling and a curriculum aligned with current workforce demands, making Merrimack a smart investment in future success.

Advance Your Career in Data Science Today

Data science is a field in which your expertise can drive real change across sectors. As industries continue to rely on data for innovation and decision-making, building a strong foundation in analytics, programming, and model development is essential for long-term success. 

Whether you’re just starting out or looking to advance your career, now is the time to take the next step with a Merrimack online graduate degree or certificate. Connect with an advisor or begin your application today to prepare for what’s next in data science.