Transitioning from Nonprofit management to Data Science?

In summary, the individual is seeking advice on transitioning into a new career after obtaining a degree in mathematics and second-guessing their decision to pursue a PhD. They discovered a passion for data science through online courses and are seeking recommendations for entering this field. The speaker advises them to research graduate programs in computer science, electrical engineering, and statistics to find a program that aligns with their interests.
  • #1
ijl
1
0
Hi all,

I am trying to figure out the best way to transition into a new career.

I obtained my undergraduate degree in mathematics in 2010. Up until the beginning of my senior year I was determined to go on to do a PhD in pure mathematics. However, I started second guessing myself when I saw a very talented student who was 2 years ahead of me drop out of his PhD program.

My motivation for going to graduate school was pretty superficial. I thought it was just what a pure math major was supposed to do. So instead of applying to grad school I signed up for a graduate level algebra course as a non-degree seeking student the following semester and began interning for a small non-profit organization. I passed the course with a B, but really didn't see a math PhD as my calling.

I enjoyed my internship, so I took a job as a manager with the non-profit instead of grad school.Currently, my job consists of writing proposals for grant funding, creating marketing materials, and managing donor/donation databases.However, I've reached a point in my career where I do not think I can gain much more from my current job. My school debts are completely paid off now and I am ready for a new challenge.

I just finished taking the first offering of Computer Science 6.00x through MIT and EDX. I loved the course. I was especially fond of programming Monte Carlo simulations to solve problems related to epidemiology. I am now signed up for a coursera course on Machine Learning through Stanford.

Data science really seems like a career I would like to pursue. Does anyone have any reccomendations for how someone of my background could enter this field? Is there a master's level program that would prepare me for this type of work?
 
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  • #2
When you say "data science" I assume you mean things like pattern recognition, machine learning and in general ways of developing algorithms to find patterns in large data sets?

If so, this is a well-established field you can study at the graduate level in C.S. or E.E. departments. I can't speak for all departments because I don't really know what defines C.S. or E.E., but these are at least pretty classic topics in C.S. There may also be overlap here with statistics. "Data science" tends to be a somewhat catch-all interdisciplinary term.

In any case, with a math B.S. and the high level of interest you clearly possess, completing an M.S. in this area should be no problem. The only tangible advice I can offer based on what you said is to do some research on various departments (CS, EE, stat, possibly others), to see what kind of research they have going on, and what courses they offer, what the professors are experts on, etc. Just research department websites as if you were a PhD applicant, so you can be sure the program has what you are looking for.
 

Related to Transitioning from Nonprofit management to Data Science?

1. What skills from nonprofit management are transferable to data science?

Some of the skills that are transferable from nonprofit management to data science include project management, communication, data analysis, and problem-solving. As a nonprofit manager, you have experience managing projects, communicating with stakeholders, analyzing data, and finding solutions to complex problems, all of which are valuable in the field of data science.

2. Do I need to have a background in computer science to transition to data science?

No, you do not necessarily need a background in computer science to transition to data science. While having a strong foundation in computer science can be helpful, it is not a requirement. Many data scientists come from diverse backgrounds such as statistics, mathematics, economics, and social sciences. However, having some knowledge of programming languages, such as Python or R, can make the transition smoother.

3. How can I gain the necessary technical skills for data science?

There are several ways to gain technical skills for data science. You can take online courses, attend workshops or boot camps, or enroll in a degree program in data science. Many universities now offer data science programs, and there are also online platforms, such as Coursera and Udemy, that offer courses specifically for data science skills. Additionally, you can practice your skills by working on personal projects or participating in data science competitions.

4. What are the key differences between nonprofit management and data science?

The key differences between nonprofit management and data science include the focus of the work, the types of skills required, and the tools and technologies used. Nonprofit management focuses on managing projects and organizations to achieve social impact, while data science focuses on using data to solve complex problems and make informed decisions. Nonprofit management requires skills in communication, teamwork, and stakeholder management, while data science requires skills in programming, statistics, and data analysis. The tools and technologies used in nonprofit management may include project management software and fundraising platforms, while data science uses programming languages, statistical software, and data visualization tools.

5. What are some tips for successfully transitioning from nonprofit management to data science?

Some tips for successfully transitioning from nonprofit management to data science include building a strong foundation in programming languages, networking with professionals in the field, and gaining hands-on experience through projects or internships. It is also important to continuously learn and stay updated on new technologies and techniques in data science. Additionally, showcasing your skills and experience through a portfolio or online presence can help you stand out to potential employers in the data science industry.

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