10 In-Demand Data Science Careers to Consider
As industries continue to recognize the transformative power of data, the need for skilled data science professionals is at an all-time high. The ability to build predictive models, perform complex analyses, and derive actionable insights from data has become critical for companies seeking a competitive edge in just about any market.
This growing field presents an exciting and rewarding path for those who are passionate about leveraging data to create solutions across a range of different professional sectors. Keep reading as we outline a handful of in-demand data science careers you could pursue.
10 Data science jobs on the rise
As organizations navigate an increasingly data-rich landscape, the demand for professionals who can harness the power of this information has reached unprecedented heights. According to the Bureau of Labor Statistics (BLS), data science jobs are expected to grow 36 percent between 2021 and 2031, which is seven times faster than the average for all occupations nationwide. These roles also come with significantly higher median annual salaries.
From healthcare and education to manufacturing and logistics, data science roles can be found in virtually any industry. Consider the following examples:
1. Operations research analyst
These professionals use advanced mathematical and analytical techniques to help organizations solve complex problems and run more efficiently. They examine data to identify and analyze inefficiencies within systems in transportation, supply chain management, construction, and other industries.
This role involves creating mathematical models, conducting simulations, and utilizing optimization techniques to improve processes, minimize costs, maximize efficiency, and ultimately enhance overall decision-making.
2. Data engineer
In data engineering positions, professionals are responsible for designing, constructing, and maintaining the systems and architectures that handle large volumes of data. They build and manage data pipelines, databases, and infrastructure, ensuring that information flows seamlessly from multiple sources into useable formats for analysis.
Data engineers often leverage tools and technologies like SQL, Hadoop, Spark, and various cloud services to manage and manipulate data effectively. They also collaborate closely with data scientists and analysts to understand data needs and create frameworks for efficient data processing.
3. Business intelligence analyst
Those who specialize in business intelligence analysis are experts at transforming raw data into actionable insights that drive strategic decisions within an organization. They collect and analyze data from various sources and use tools like SQL, Tableau, or Power BI to create meaningful visualizations, dashboards, and reports.
By interpreting these data outputs, business intelligence analysts help stakeholders understand market trends, consumer behavior, and operational performance. This work ultimately aids in the optimization of business processes and the achievement of organizational goals.
4. Cybersecurity analyst
These data science professionals are tasked with safeguarding an organization’s systems, networks, and data from potential cyber threats and attacks. Cybersecurity analysts monitor and analyze security measures, continuously assessing vulnerabilities and possible risks to preemptively identify and mitigate security breaches.
In addition to developing and implementing security protocols, their role also involves staying up to date on the latest security trends, tools, and technologies to proactively ensure the resilience and integrity of an organization’s digital infrastructure.
5. Computer and information research scientist
Working at the forefront of technological innovation, these professionals conduct groundbreaking research to solve complex problems and push the boundaries of computing. Computer and information research scientists explore new algorithms and systems to advance fields like artificial intelligence (AI), machine learning, cryptography, and more.
Their work involves creating new technologies, improving existing systems, and contributing to scientific knowledge that drives technological advancements.
6. Healthcare analyst
This data science role is responsible for leveraging data to improve the efficiency and effectiveness of healthcare delivery. Healthcare analysts gather, analyze, and interpret data from many sources, such as patient records, billing systems, and clinical trials to derive insights that enhance patient care, operational workflows, and cost-efficiency.
These professionals collaborate with diverse stakeholders to create reports, visualizations, and predictive models that identify patterns, trends, and opportunities for improvement within healthcare organizations.
7. Machine learning engineer
A sector of AI, machine learning focuses on enabling systems to learn and improve from experience without being explicitly programmed for each alteration. Those who pursue roles as machine learning engineers specialize in developing algorithms and models that allow computers to analyze and interpret data, recognize patterns, and make decisions or predictions based on that data.
They work the entire machine learning pipeline, from data collection and processing to model development, training, and deployment in production environments, often working closely with data scientists and software engineers.
8. Quantitative analyst
These data science professionals apply mathematical and statistical techniques to financial and risk management problems. They work extensively with financial data to develop and implement mathematical models, algorithms, and trading strategies that aid in pricing securities, managing risk, and optimizing investment portfolios.
Quantitative analysts utilize their expertise in mathematics, programming, and financial theory to analyze market trends, evaluate financial instruments, and create models that assist traders, portfolio managers, and financial institutions in making informed decisions.
9. AI research scientist
Critical to widespread efforts to advance the capabilities of artificial intelligence, AI research scientists conduct in-depth research and delve into cutting-edge techniques in machine learning, deep learning, natural language processing, and more. They design and execute experiments, analyze data, and contribute to academic literature by publishing their findings.
The work of an AI research scientist involves solving complex problems, improving the performance of AI algorithms, and exploring novel applications with the goal of driving the field’s evolution forward.
10. Market research analyst
Professionals who pursue careers in market research analysis play an important role in studying market conditions, consumer behaviors, and trends to provide valuable insights that help businesses make informed decisions. They collect and analyze data through various methods, including surveys, interviews, and statistical analysis.
Market research analysts evaluate this data to create reports, forecasts, and presentations that help organizations understand their target audience, optimize marketing strategies, and identify new opportunities for growth.
Pave the way for a successful future in data science
It’s clear that organizations across industries are actively seeking skilled data science professionals to help improve efficiencies and make more impactful decisions across their operations. If you’re looking to gain the knowledge and skills you need to qualify for the in-demand data science careers listed above, there is no better time than now.
A graduate degree in data science can equip professionals like you with a deep understanding of data analysis and interpretation, opening the door to a multitude of high-growth career opportunities.
You can learn more about what these dynamic post-baccalaureate programs entail in our article “What to Expect from an Online Data Science Master’s Degree.”
