More than a career pathway

Data science is quickly becoming one of the most important disciplines of the modern world — not only as a career pathway, but also as a way of thinking and solving problems across nearly every industry. For educators and those involved in career readiness, it offers a rich opportunity to connect classroom learning to real-world challenges and future jobs.

At its core, data science is the process of using data to identify patterns, make predictions, and drive decisions. It blends mathematics, statistics, computer science, and domain-specific knowledge. In practical terms, it’s like detective work — with data serving as the clues.

What Data Scientists Do — and Why It Matters in the Classroom

Data scientists work across industries, analyzing information from a wide range of sources — websites, apps, social media, sensors, business transactions, and scientific instruments — to develop insights that inform critical decisions. Their process typically involves:

Collecting Data – From apps, surveys, sensors, and digital platforms.
Example: A streaming service logs what users watch, when they pause, and what they rate.

Cleaning the Data – Fixing errors, removing duplicates, and organizing information.
Example: A sports analytics team filters out incomplete or inaccurate statistics before analysis.
Analyzing the Data – Using mathematical models and statistics to identify trends.
Example: Meteorologists analyze historical weather patterns to improve hurricane forecasts.
Building Predictive Models – Leveraging programming and machine learning to forecast outcomes.
Example: An e-commerce platform recommends products based on past behavior.
Visualizing the Data – Creating graphs, dashboards, and maps to communicate findings clearly.
Example: Public health officials track infection trends on a regional heat map.
Solving Real-World Problems – Applying insights to improve systems and outcomes.
Example: Hospitals use data models to identify patients at higher risk for complications.

For more examples of how data scientists – and educators, too! – actually carry out these kinds of data operations, take a look at this catalogue of data science tools for education.

Where the Data Comes From

In today’s digital world, data is generated by nearly every human activity. Understanding its sources helps frame how data literacy connects to students’ daily lives and long-term career options.

Internet Use – Search queries, clicks, social media activity
Sensors & Devices – Smartwatches, thermostats, and GPS-enabled tools
Retail & Business Systems – Purchase histories, customer feedback, loyalty programs
Social Media – Content trends, hashtag usage, video interactions
Science & Nature – Satellites, ocean buoys, and environmental monitors
Everyday Technology – Phone location services, streaming platforms, traffic cameras

Believe it or not! The volume of data generated globally has grown faster in the last two years than at any point in human history — a trend expected to accelerate.

The Intersection of Data Science and AI

Artificial intelligence and data science work hand-in-hand. Data science supplies the data and analysis; AI uses that data to make predictions or decisions — often in real time.

Case Study: Preventing Credit Card Fraud
Data science identifies normal spending patterns based on geography, time, and amount.
AI uses this information to detect anomalies and respond instantly.
If a suspicious purchase occurs, AI can flag or block it automatically and alert the cardholder.

The more data an AI system receives, the more accurate it becomes — learning from millions of examples to improve fraud detection and reduce false alarms. North Carolina State University showcases work that educators in the state have done to illustrate more ways that data science and AI work together.

Pathways Into Data Science Careers

Traditional pathways into data science often begin with bachelor’s degrees in data science, statistics, or related fields. However, there are increasingly accessible alternatives: associate degrees, online certifications, and hands-on experience with coding and data analysis tools.

Entry-Level Roles Include:

Junior Data Analyst
Data Technician
Research Assistant

These positions often require a foundation in coding (Python, R, SQL), a basic understanding of statistical methods, and the ability to work with data visualization tools. Check out the Data Scientist Roadmap and Harvard Engineering’s discussion of career options in the field to learn more.

Skills and Dispositions That Support Data Science Learning

Data science is not only technical. It draws heavily on cognitive, interpersonal, and ethical competencies — many of which are already developed in classroom settings:

Curiosity & Critical Thinking
Formulating questions and testing hypotheses
Detecting patterns and inconsistencies
Communication & Collaboration
Explaining complex ideas clearly
Working in interdisciplinary teams
Responsibility & Ethics
Considering the fairness of algorithms
Understanding data privacy and consent
Data Storytelling & Visualization
Translating data into charts, infographics, or interactive displays
Connecting quantitative findings to real-world issues

Educators play a key role in helping students see data not as abstract numbers, but as a tool for inquiry, discovery, and meaningful impact.

Bringing Data Science Into the Classroom

There are many ways to integrate data science concepts into existing curricula:

Math: Analyzing real-world data sets to practice statistics
Science: Using environmental or health data for lab activities
Computer Science: Coding simulations or building simple AI models
Social Studies: Investigating trends in voting, economics, or public policy
CTE/STEM Programs: Offering focused courses or credentials in data analytics

Free resources and platforms such as YouCubed High School Data Science, the Introduction to Data Science Project, and Data Science 4 Everyone offer curriculum-aligned content and professional development for educators.

Our latest publication! Explore Careers in Data Science

Data science offers multiple career options — from technical programming to ethical analysis and storytelling. Whether students lean toward math, the humanities, or digital media, this field provides a growing number of career pathways that intersect with their strengths and interests. Our newest publication, Explore Careers in Data Science, is a great starting point for educators and outreach teams looking to introduce the field to high school students of all backgrounds and interests. Besides offering an accessible, comprehensive overview of data science itself, the book goes in depth on data science-related career options in fields as diverse as healthcare, entertainment, conservation, and finance. And for use in the classroom or other learning environments, an interactive Student Workbook is available for free!

Be in touch with any questions, and please share any comments or feedback on your experiences with data science learning activities, too!

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Eric Iversen is VP for Learning and Communications at Start Engineering. Comments and feedback are always welcome.

Our goal at Start Engineering is to help make STEM careers imaginable and accessible to kids of all backgrounds and interests. We publish educational and career outreach books in STEM fields like engineering, cybersecurity, and biotechnology, with more topics to come. Check out our newest releases here!

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