Recent Graduate Planning Fall 2026 Master’s — Advice Needed

[omhirani]

I graduated in 2025 with a degree in Artificial Intelligence and Data Science and am planning to pursue a Master’s in Quantitative/Computational Finance in Fall 2026 (or possibly Spring 2027). I’d really appreciate insights from current students, alumni, and professionals regarding:

• Coming as a fresher:
  Is it advisable to come directly to the U.S. for a master’s without prior work experience? Or do employers and programs strongly prefer candidates who already have industry exposure?
• Recruitment prospects:
  Do companies in quant finance (trading, research, risk, data science roles) actively recruit fresh master’s graduates with no prior internships or full-time work experience?
  What are the realistic chances of getting interviews and landing roles straight out of a master’s program?
• Fall vs. Spring intake:
  I’ve heard that students starting in Fall need to begin internship applications almost from day one, while Spring students often have an extra semester before recruiting begins. Is this true in practice?
  Which intake provides better opportunities to secure internships and full-time roles?
• Visa considerations:
  How is the current U.S. visa situation (OPT, CPT, H-1B) impacting fresh graduates? Are companies becoming more selective about sponsoring international students?

 

[Nickie]

If you can, aim for Fall 2026, build a strong portfolio before arriving, and use your first semester aggressively to network and prepare for internship recruiting. Work experience helps, but you can compensate with strong projects, networking, and clear domain focus.

 

[omhirani]

Thanks a lot for the advice @Nickie ! That makes sense — I’ll target Fall 2026 and focus on strengthening my portfolio before joining. When you say ‘strong portfolio,’ do you mean finance-specific projects (like trading strategies, risk models) or a mix of data science/AI projects with a finance angle? Would love to hear what worked well for you or your peers.

 

[Nickie]

By “strong portfolio,” I mean projects that clearly demonstrate both your technical depth and your ability to apply those skills in finance—so ideally a mix of finance-specific work (like backtesting trading strategies, portfolio optimization, risk modeling, or derivative pricing) and data science/AI projects with a finance angle (such as sentiment analysis of market news, volatility forecasting, or anomaly detection for fraud). This combination shows recruiters that you’re not just strong in coding and ML but can directly translate those skills into quantitative finance problems, which is exactly what worked well for many of my peers who landed quant roles.

I would suggest you to do a bit more research and talk to others as well before taking a final decision because what I suggest was my personal opinion and it may not end up as your expectations. Just to make sure you do not misunderstand anything.