MSCS or MSDS for a Data Scientist?
Published:Dec 29, 2025 01:27
•1 min read
•r/learnmachinelearning
Analysis
The article presents a dilemma faced by a data scientist deciding between a Master of Computer Science (MSCS) and a Master of Data Science (MSDS) program. The author, already working in the field, weighs the pros and cons of each option, considering factors like curriculum overlap, program rigor, career goals, and school reputation. The primary concern revolves around whether a CS master's would better complement their existing data science background and provide skills in production code and model deployment, as suggested by their manager. The author also considers the financial and work-life balance implications of each program.
Key Takeaways
- •The decision hinges on whether to prioritize skills in software engineering and model deployment (MSCS) or reinforce existing data science knowledge (MSDS).
- •Factors include program reputation, cost, work-life balance, and potential career trajectory (e.g., moving into MLE roles).
- •The author's personal preferences (dislike of data structures) and career goals (uncertainty about staying in tech) also influence the decision.
Reference
“My manager mentioned that it would be beneficial to learn how to write production code and be able to deploy models, and these are skills I might be able to get with a CS masters.”