Can you become an Applied Data Scientist without a degree?
An alternative career path to becoming an Applied Data Scientist with its major challenges, possible benefits, and some ways to hack your way into it.
Yes, it is possible to become an Applied Data Scientist without a degree. While a formal degree in a related field can provide a solid foundation, it is not the only path to a successful career in data science. Many employers in the industry value practical skills and hands-on experience over formal education.
How to achieve a career as an Applied Data Scientist without a degree?
-
Develop a strong foundation in mathematics and statistics: Data science heavily relies on mathematical and statistical concepts. Take online courses or self-study to build a solid understanding of linear algebra, calculus, probability, and statistics.
-
Learn programming languages: Proficiency in programming is crucial for data scientists. Start with Python, as it is widely used in the field. Learn the basics of data manipulation, analysis, and visualization libraries such as NumPy, Pandas, and Matplotlib.
-
Master machine learning techniques: Gain a deep understanding of machine learning algorithms and techniques. Learn how to implement them using libraries like Scikit-learn. Practice by working on various projects and datasets to develop practical skills.
-
Build a strong portfolio: Create a portfolio of data science projects to showcase your skills and expertise. Start with small projects and gradually work on more complex ones. Share your projects on platforms like GitHub or Kaggle to gain visibility and demonstrate your abilities to potential employers.
-
Network and collaborate: Engage with the data science community by participating in online forums, attending meetups, and joining relevant social media groups. Collaborate with others on projects to gain practical experience and expand your network.
-
Gain practical experience through internships or freelance work: Look for internships or freelance opportunities that allow you to apply your skills in real-world scenarios. This will not only provide valuable experience but also enhance your resume.
Hacks and advice for becoming an Applied Data Scientist without a degree:
-
Take online courses and certifications: Enroll in online courses and certifications offered by reputable platforms like Coursera, edX, or Udacity. These courses can provide structured learning and help you acquire industry-relevant skills.
-
Participate in Kaggle competitions: Kaggle is a platform that hosts data science competitions. Participating in these competitions can help you sharpen your skills, learn from others, and gain recognition within the data science community.
-
Contribute to open-source projects: Contribute to open-source projects related to data science. This not only allows you to work on real-world projects but also helps you collaborate with experienced professionals and gain visibility.
-
Attend data science bootcamps: Consider joining data science bootcamps that offer intensive, hands-on training programs. These bootcamps often focus on practical skills and can provide a fast-track to gaining the necessary knowledge and experience.
Difficulties and benefits of pursuing a career as an Applied Data Scientist without a degree:
Difficulties: - Lack of formal credentials may limit opportunities with certain employers who prioritize degrees. - It may be challenging to compete with candidates who have formal education and degrees. - Self-learning requires discipline and motivation, as there is no structured curriculum or guidance.
Benefits: - Practical skills and experience can be valued more than formal education by many employers. - The ability to showcase a strong portfolio of projects can demonstrate your capabilities effectively. - The flexibility to learn at your own pace and focus on specific areas of interest.
Differences compared to a conventional or academic path:
Compared to a conventional or academic path, pursuing a career as an Applied Data Scientist without a degree may require more self-motivation and determination. However, it also offers the advantage of focusing on practical skills and gaining hands-on experience. This approach allows you to tailor your learning to specific areas of interest and potentially accelerate your career progression. Additionally, the ability to showcase a strong portfolio can be a significant advantage when competing for job opportunities. However, it's important to note that some employers may still prefer candidates with formal degrees, so it's essential to continuously update your skills and stay up-to-date with industry trends.
Data Engineer
@ murmuration | Remote (anywhere in the U.S.)
Full Time Mid-level / Intermediate USD 100K - 130KSenior Data Scientist
@ murmuration | Remote (anywhere in the U.S.)
Full Time Senior-level / Expert USD 120K - 150KVice President of Application Development
@ DrFirst | United States
Full Time Executive-level / Director USD 200K - 280KMedical Countermeasure Development SME
@ Noblis | Reston, VA, United States
Full Time USD 132K - 206KPlanner, Technical Lead Manager (Router)
@ Waymo | Mountain View (US-MTV-RLS1)
Full Time Senior-level / Expert USD 272K - 346K