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How was your major helpful for your career?
Hi,
I am currently interested in Data Science, though not many UC offer as a major so I was thinking of majoring in Economics.
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5 answers
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Dr’s Answer
Hey CK,
HONESTLY, I haven’t been deep in that world myself, but funny enough, I actually considered data science before diving into medicine. Along the way, I’ve met plenty of people in economics, politics, and tech, so here’s what I can tell you, CK…
Economics is actually a solid foundation for data science, especially if you're into analytics, finance, or policy work. A lot of data science is about making sense of numbers, trends, and human behavior—exactly what economics teaches you. The only catch? You’ll need to supplement it with programming skills (Python, R, SQL) and some stats-heavy coursework.
If you’re set on data science but UCs don’t offer it as a major, don’t stress. Plenty of data scientists start from economics, math, engineering, or even biology. The key is building real-world experience—internships, projects, and online courses—so that by the time you graduate, your skills do the talking.
Soooo.. Short answer: Yes, but with caveats. Economics is a strong foundation for data science, but it’s not a direct replacement for a data science degree. You’ll need to be proactive in filling some skill gaps.
Why Economics Can Work for Data Science
Strong Analytical Training – You’ll learn to interpret data, recognize trends, and understand behavior, all of which are crucial for data science.
Heavy on Stats & Math – If you take courses in econometrics, probability, and modeling, you’ll have a solid quantitative foundation.
Flexibility in Careers – Economics majors can pivot into finance, consulting, policy analysis, or tech, keeping your options open.
Great for Business-Oriented Data Science – If you’re into financial analytics, market research, or business intelligence, economics is a strong match.
Where Economics Falls Short
Limited Coding Exposure – Unlike CS or data science majors, econ won’t teach you Python, R, or SQL by default. You’ll have to learn them on your own.
Weaker Machine Learning Foundations – Econometrics is useful, but it’s not a full substitute for AI, ML, and big data techniques.
Competitive Job Market – With just an econ degree and no coding or projects, you might struggle against CS or stats majors when applying for data science roles.
How to Make Economics Work for Data Science
1. Take More Stats & Math – Load up on econometrics, statistics, and calculus. Strong math skills will set you apart.
2. Learn to Code ASAP – Python and R are must-haves, and SQL is highly useful. Start with free platforms like Kaggle, DataCamp, or Coursera.
3. Pick Up Some CS or Data Science Courses – Even if your school doesn’t offer a DS major, take electives in programming and data analytics.
4. Build a Portfolio – Get hands-on experience through independent projects, Kaggle competitions, or internships. Show what you can do.
5. Network & Intern – Many econ students break into data science through internships in analytics, finance, or policy research.
If you love economics, go for it—but make sure to add the technical skills. If your main goal is data science, try to mix in CS and stats courses or even consider a double major. Either way, be proactive, build your skills, and you’ll be in a strong position.
Hope that helps, CK! If you ever want more insight, feel free to reach out. Good luck!
If you love economics, go for it, but be intentional about picking up programming and data-related skills.
If your heart is set on data science, check if your university offers a double major or minor in CS, statistics, or applied math.
If you’re unsure, major in economics with a strong quantitative focus, take extra CS and data science classes, and keep your options open.
HONESTLY, I haven’t been deep in that world myself, but funny enough, I actually considered data science before diving into medicine. Along the way, I’ve met plenty of people in economics, politics, and tech, so here’s what I can tell you, CK…
Economics is actually a solid foundation for data science, especially if you're into analytics, finance, or policy work. A lot of data science is about making sense of numbers, trends, and human behavior—exactly what economics teaches you. The only catch? You’ll need to supplement it with programming skills (Python, R, SQL) and some stats-heavy coursework.
If you’re set on data science but UCs don’t offer it as a major, don’t stress. Plenty of data scientists start from economics, math, engineering, or even biology. The key is building real-world experience—internships, projects, and online courses—so that by the time you graduate, your skills do the talking.
Soooo.. Short answer: Yes, but with caveats. Economics is a strong foundation for data science, but it’s not a direct replacement for a data science degree. You’ll need to be proactive in filling some skill gaps.
Why Economics Can Work for Data Science
Strong Analytical Training – You’ll learn to interpret data, recognize trends, and understand behavior, all of which are crucial for data science.
Heavy on Stats & Math – If you take courses in econometrics, probability, and modeling, you’ll have a solid quantitative foundation.
Flexibility in Careers – Economics majors can pivot into finance, consulting, policy analysis, or tech, keeping your options open.
Great for Business-Oriented Data Science – If you’re into financial analytics, market research, or business intelligence, economics is a strong match.
Where Economics Falls Short
Limited Coding Exposure – Unlike CS or data science majors, econ won’t teach you Python, R, or SQL by default. You’ll have to learn them on your own.
Weaker Machine Learning Foundations – Econometrics is useful, but it’s not a full substitute for AI, ML, and big data techniques.
Competitive Job Market – With just an econ degree and no coding or projects, you might struggle against CS or stats majors when applying for data science roles.
How to Make Economics Work for Data Science
1. Take More Stats & Math – Load up on econometrics, statistics, and calculus. Strong math skills will set you apart.
2. Learn to Code ASAP – Python and R are must-haves, and SQL is highly useful. Start with free platforms like Kaggle, DataCamp, or Coursera.
3. Pick Up Some CS or Data Science Courses – Even if your school doesn’t offer a DS major, take electives in programming and data analytics.
4. Build a Portfolio – Get hands-on experience through independent projects, Kaggle competitions, or internships. Show what you can do.
5. Network & Intern – Many econ students break into data science through internships in analytics, finance, or policy research.
If you love economics, go for it—but make sure to add the technical skills. If your main goal is data science, try to mix in CS and stats courses or even consider a double major. Either way, be proactive, build your skills, and you’ll be in a strong position.
Hope that helps, CK! If you ever want more insight, feel free to reach out. Good luck!
Dr recommends the following next steps:
Thank you, this is an amazing breakdown! I have already been thinking about a lot of what you wrote.
CK
CK, looks like your brain was already cooking up the good stuff before I even got here! Trust that instinct—it’s sharper than a brand-new scalpel. Keep going, and soon, you'll be the one dropping wisdom bombs on everyone else man! 😉😎
Dr H
Thank you, Doc Frick! Your encouragement never fails to lift my spirits. Let's keep pushing forward together!
Dr H
Updated
Emmanuel’s Answer
Choosing a career path can be a daunting task, but considering the following factors can help you make an informed decision:
1. Interests and Passions
- What activities do you enjoy doing in your free time?
- What subjects do you find most fascinating?
2. Skills and Strengths
- What are your natural talents?
- What skills have you developed over time?
3. Values and Priorities
- What matters most to you in a career? (e.g., work-life balance, creativity, financial stability)
- What kind of work environment do you prefer?
4. Job Market and Growth Opportunities
- Is the field you're interested in growing or declining?
- Are there opportunities for advancement and professional development?
5. Education and Training Requirements
- What level of education or training is required for your desired career?
- Are there any certifications, licenses, or specializations needed?
6. Salary and Benefits
- What is the average salary range for your desired career?
- What benefits, such as health insurance or retirement plans, are typically offered?
7. Work-Life Balance and Flexibility
- How many hours per week can you expect to work?
- Are there opportunities for flexible scheduling or remote work?
8. Personal Fulfillment and Purpose
- How will your career align with your values and goals?
- Will you feel a sense of purpose and fulfillment in your work?
9. Networking Opportunities
- Are there opportunities to connect with professionals in your desired field?
- Can you attend industry events, conferences, or job fairs?
10. Long-term Prospects
- Where do you see yourself in 5-10 years?
- Are there opportunities for career advancement or entrepreneurship?
By considering these factors, you'll be better equipped to choose a career path that aligns with your goals, values, and aspirations.
1. Interests and Passions
- What activities do you enjoy doing in your free time?
- What subjects do you find most fascinating?
2. Skills and Strengths
- What are your natural talents?
- What skills have you developed over time?
3. Values and Priorities
- What matters most to you in a career? (e.g., work-life balance, creativity, financial stability)
- What kind of work environment do you prefer?
4. Job Market and Growth Opportunities
- Is the field you're interested in growing or declining?
- Are there opportunities for advancement and professional development?
5. Education and Training Requirements
- What level of education or training is required for your desired career?
- Are there any certifications, licenses, or specializations needed?
6. Salary and Benefits
- What is the average salary range for your desired career?
- What benefits, such as health insurance or retirement plans, are typically offered?
7. Work-Life Balance and Flexibility
- How many hours per week can you expect to work?
- Are there opportunities for flexible scheduling or remote work?
8. Personal Fulfillment and Purpose
- How will your career align with your values and goals?
- Will you feel a sense of purpose and fulfillment in your work?
9. Networking Opportunities
- Are there opportunities to connect with professionals in your desired field?
- Can you attend industry events, conferences, or job fairs?
10. Long-term Prospects
- Where do you see yourself in 5-10 years?
- Are there opportunities for career advancement or entrepreneurship?
By considering these factors, you'll be better equipped to choose a career path that aligns with your goals, values, and aspirations.
Thank you! These are crucial factors I will continue to consider as I apply to college and enter the workforce.
CK
Updated
Bright’s Answer
Economics is a great alternative to Data Science due to its emphasis on statistical analysis, modeling, and problem-solving skills. Combining your Econ major with electives in programming and statistics can enhance your data science skills. Some UC schools, like Berkeley, San Diego, and Davis, offer quantitative economics programs that incorporate data analysis. Consider a minor or double major in a related field like Statistics or Computer Science to further strengthen your data science background.
Thank you for the advice.
CK
Updated
Sneha’s Answer
Hi CK!Majoring in Data Science and Business Analytics has been incredibly beneficial for my career. These fields provided me with a strong foundation in handling data, using tools like Python and SQL, and applying analytical techniques to solve real-world problems. Even if your major is Economics, you'll find that the skills you learn like understanding data patterns and making data-driven decisions—are highly transferable to data science roles. Economics will give you a great backdrop in analytical thinking and problem-solving, which are key in data science. Good luck!
I appreciate this, thank you for the advice.
CK
Kerlyn Mottershead
Technical Program Manager, BS in Data Science
1
Answer
Updated
Kerlyn’s Answer
Hi, I majored in Computer Science with a focus on Data Science. Not many universities in some areas offer this as a major, but many online universities do. Another option is to major in Statistics or Applied Statistics, though they might not have many programming courses. You might need to take electives in Python or R, or learn through MOOCs (Massive Open Online Courses) on sites like Udemy and Coursera, which offer Data Science specializations and certifications. You could also consider majors in Machine Learning or Data Analytics. I hope this helps. For fun, you can check out this video game that simulates being a Machine Learning engineer without coding: https://luden.io/wtl/
I appreciate this, thank you for the advice.
CK