Data and Technology

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Data and Technology

Cognitive Science Career Pathways

What is Data and Technology?

This broad field focuses on how information is collected, processed, analyzed, and applied through digital systems to solve problems and improve decision-making. It includes areas such as data science, software and system design, user experience, and artificial intelligence, all of which work together to create tools and technologies that shape how people interact with information and with each other. This field is driven by both technical innovation and real-world application, with an emphasis on improving efficiency, understanding complex systems, and designing solutions that meet human and organizational needs.

Cognitive Science in Practice

Cognitive Science plays an important role in data and technology by informing how people perceive information, make decisions, and interact with digital systems. It helps guide the design of tools, models, and interfaces that align with human thinking, making technology more intuitive, usable, and effective. It also supports the development and interpretation of data-driven systems by considering how people understand patterns, process complexity, and respond to information in real-world contexts.

Data and Technology for Cognitive Science Majors

Explore sub-fields of Data and Technology that are fit for cognitive science majors. Click on the hyperlinked sample job posts to see real job postings that detail the position's responsibilities and qualifications. 

  • Data Science & Analytics
  • About Field
    Data Science & Analytics focuses on collecting, analyzing, and interpreting data to identify patterns, solve problems, and support decision-making. It combines statistical methods, programming, and visualization tools to turn complex information into clear, actionable insights used across industries such as business, healthcare, and technology.

    Sample Job Posts
    • Data Scientist
    • Research Data Analyst
    • Hospital Operations Business Intelligence Analyst
    • Data Analyst

    Sample Job Titles
    Operations Analyst, Data Engineer, Analytics Specialist
  • User Experience (UX/UI) and Design
  • About Field
    User Experience (UX) and Design focuses on creating intuitive, accessible, and effective products and systems based on how people think, behave, and interact with technology. It involves research, testing, and design principles to improve usability, enhance user satisfaction, and ensure that digital tools meet human needs.

    Sample Job Posts
    • UX Designer
    • UX Writer
    • Interaction Designer

    Sample Job Titles
    UX Researcher, Product Designer, Information Architect, Visual Designer, Design Engineer, Front-End Developer
  • Machine Learning/Artificial Intelligence
  • About Field
    Machine Learning and Artificial Intelligence focuses on building systems that can learn from data, recognize patterns, and make predictions or decisions with minimal human input. It combines computer science, mathematics, and data-driven modeling to develop technologies used in automation, language processing, recommendation systems, and intelligent software applications.

    Sample Job Posts
    • Artificial Intelligence/Machine Learning Engineer
    • Artificial Intelligence/Machine Learning Software Developer

    Sample Job Titles
    Machine Learning Analyst, Machine Learning Operations Engineer, Algorithm Engineer

How to Prepare for a Career in Data and Technology

Do your Research

The steps you take to prepare for a career in business depend on what kind of position you want to pursue. For an overview on how to conduct research on your professions of interest, look at our Work Research section on the right. Here are some other starting points:

 

Supplement Your Bachelor's Degree

Consider the following course, double major, minor, and experiential recommendations during your academic journey

  • Cognitive Science Major Course Recommendations
  • Group A: Cognitive Science Topical
    PSC 100 — Introduction to Cognitive Psychology
    PSC 130 — Human Learning & Memory (also Group F)
    PSC 133 — Neuroeconomics/Reinforcement Learning & Decision Making (also Group C)
    PSC 134 — Computational Cognitive Neuroscience (also Group C)
    LIN 177 — Computational Linguistics (also Group B)
    NPB 167 — Computational Neuroscience (also Group B)
    PHI 133 — Logic, Probability, & Artificial Intelligence (also Group B)
    ECS 170 — Introduction to Artificial Intelligence (also Group B)

    Group B: Computation
    ECS 120 — Theory of Computation
    ECS 171 — Machine Learning

    Group F: Psychology
    PSC 103A — Statistical Analysis of Psychological Data
    PSC 103B — Statistical Analysis of Psychological Data
    PSC 137 — Neurobiology of Learning Memory
    PSC 140 — Developmental Psychology
    PSC 141 — Cognitive Development

    Group G: Breadth (CGS AB)
    HDE 161 — Technology Use, Health, & Aging
    STA 106 — Applied Statistical Methods: Analysis of Variance
    STA 106 — Applied Statistical Methods: Regression Analysis
    STA 141A — Fundamentals of Statistical Data Science
  • Double Major Recommendations
  • Applied Mathematics
    Business
    Communication
    Computer Engineering
    Computer Science
    Computer Science and Engineering
    Data Science
    Design
    Linguistics
    Mathematical Analytics and Operations Research
    Mathematical and Scientific Computation
    Neurobiology, Physiology and Behavior
    Philosophy
    Psychology
    Science & Technology Studies
    Statistics
  • Minor Recommendations
  • Business
    Computer Science
    Communication
    Data in Society
    History and Philosophy of Science
    Linguistics
    Mathematics
    Neuroscience
    Philosophy
    Psychology
    Social Science Data Analysis and Visualization
    Statistics
  • Work Experience and Internship Recommendations
  • It is highly recommended that all undergraduate students engage in part-time work, internships, volunteering, and other extracurricular opportunities. ANY experience is RELEVANT experience.

    General Experiential Education Recommendations for Cognitive Science Students

    Data and Technology Experience Specific Recommendations
    • Get involved with the many student organizations in the tab below through their events and project opportunities
    • Check out Hack Davis for open roles on their team
    • Look into research opportunities with CGS Affiliated faculty who are in the computer science department or instructors of your Group B courses
    • Find internships for UX/UI design with the UX/UI Jobs Board
  • Campus Organization Recommendations

  • Aggie Sports Analytics
    Aggie Sports Analytics is a student-led organization pioneering the future of sports technology. We unite driven students from diverse academic backgrounds to develop innovative solutions across business, technology, and media.

    AI Student Collective @ UC Davis
    The AI Student Collective is a national network of student organizations dedicated to providing accessible AI & tech literacy through professional development programs and events.

    CodeLab
    CodeLab is a software and design agency at UC Davis, working on impactful software projects with industry clients. Our organization is the first of its kind at UC Davis, with our 3 core principles being Community, Education, and Professional Development.

    Cognitive Science Student Association at UC Davis
    As UC Davis’s only Cognitive Science community, CSSA aims to empower students by: Defining the field of Cognitive Science and what it means to be involved in the major, introducing students to the various fields and career paths in Cognitive Science, and facilitating connections between students and alumni/faculty/professionals in the field.

    Davis Data Driven Change
    Davis Data Driven Change (D3C) is a student organization that brings together students from diverse academic backgrounds to create projects focused on social impact, activism, and community change. 

    Davis Design Interactive
    Davis Design Interactive is UC Davis’s first human-centered design organization. Our organization was founded out of a growing need to provide human-centered design and user experience opportunities to students exploring the field.

    Google Developer Student Club at UC Davis
    GDSC organizes and facilitates workshops on university campuses to provide students with technical development skills.

    Girls Who Code at UC Davis
    The Girls Who Code at UC Davis college chapter program connects young women and non-binary people who are interested in tech to build a supportive community that helps them persist and succeed in the field.

    HackDavis
    Our purpose is to build and facilitate a culture of creating and pursuing diverse social good projects outside the classroom, unlock the innovative spirit of students, and connect builders across different interests. 

    #include
    We serve two main purposes: to support local organizations by delivering high quality custom web solutions to establish their web presence, and to provide a collaborative environment where students of all skill levels can learn the fundamentals of web programming and UI/UX design.

    Neurotech@Davis
    Neurotech@Davis is a student-led organization at UC Davis whose mission is to facilitate the advancement and awareness of neurotechnology by providing undergraduates with the opportunity to foster skills in this industry.

    Women in Computer Science
    Women in Computer Science (WiCS) supports, empowers and motivates the growing community of women in computer science. We aim to prepare women for the tech industry, in addition to inspiring women to explore educational and professional opportunities in computing through creating a powerful community, providing mentorship and helping them to succeed. 

Graduate School for Data and Technology

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What is Graduate School? What is a Graduate Degree?

Understand what graduate school is with this page from the Pre-Grad Advising Office. Pre-Grad Advisors are available to meet with students to discuss if graduate school is right for you .

Do I Need Graduate School for Data and Technology?

Whether you need graduate school depends on the type of role you want to pursue within data and technology. Some entry-level positions in data analysis, UX/UI design, product support, research assistance, and early-stage machine learning or analytics roles can be entered with a bachelor’s degree. 

Graduate school is more commonly recommended for more specialized, research-intensive, or highly technical roles in the field. Careers in machine learning engineering, artificial intelligence research, advanced data science, human-computer interaction research, and algorithm development often prefer or require a master’s degree or PhD, especially in industry research labs or academic settings.

Before pursuing graduate school, students are encouraged to explore job postings, build technical and design skills, complete internships or research experiences, and identify whether advanced education is necessary for their long-term goals.

Common Graduate Programs Related to Data and Technology

  • Data Science
  • Computer Science
  • Human-Computer Interaction
  • UX/UI Design
  • Artificial Intelligence
  • Machine Learning
  • Cognitive Science
  • Statistics
  • Information Science