u/quant-alchemist

Hi everyone, looking for some brutal honesty and guidance from the professionals here regarding my next career move.

My Background:

• Profile: 34M based in India.
• Education: Bachelors in Mechanical Engineering + a 1-year Diploma in Data Science.
• Experience: 4 years as a Data Analyst (heavy Python, SQL, Tableau, and advanced Excel).
• Current Situation: I took a career break starting in May 2024 due to health reasons and used this time to upskill and learn machine learning.\
• And due to this Career Break, I am having a tough time getting past preliminary HR calls and unable to land any interviews.

My Goal:

I want to pivot into Quant Risk, or FinTech, or Data Science/MLOps (bridging the gap between heavy data/tech and financial markets).

I am currently staring down two very different paths to end my career gap and make this pivot, and I don't want to waste the next 6-12 months on the wrong one.

Option A: The FRM Route

I start grinding for FRM Part 1. My plan would be to use Kaplan notes and supplement with some external probability/stats courses since my pure math background is decent but not at a "quant math major" level.

• My fear: I’ve heard the failure rate is brutal for non-finance folks, and I'm worried about sinking hundreds of hours into it only to fail.

Option B: The MSCS Route (Georgia Tech OMSCS)

I target an online MS in Computer Science (specifically GT OMSCS). To guarantee admission with my Mechanical Bachelors, I would spend the next few months taking accredited, graded prerequisite CS classes (like C++ and Data Structures) before applying, and then go all-in on the Master's.

• My fear: It's a longer academic commitment, though it directly builds the tech skills (Python, ML, Systems) needed for the roles I want.
• I can start applying for jobs as soon as I get in the Masters program.

My Questions for the Community:

1. If I take the FRM Part 1 with my proposed study stack (Kaplan + basic Probability & Statistics prep), what are the realistic chances of passing on the first attempt? Am I underestimating the math?
2. If I can't clear in the first attempt, would I be able to clear in the 2nd? Will the knowledge I gain from FRM 1 attempts be of any use? Help me land any jobs in case I can't clear the FRM 1?
3. In the Asian/Indian financial hubs, would a top-tier MSCS (like Georgia Tech) yield a higher ROI and better employer trust for my target roles than the FRM?
4. The preparation - c, c++, computer science knowledge I gain while preparing for GT OMSCS would help me in the long run, and if I am admitted into the Masters at GT, I feel i would land interviews and job opportunities and dont have to wait until the end of the program. Is my thinking correct?

I really appreciate any insights you all can provide.

P.S. I am unable to do Masters in Financial Engineering because at my current capabilities I feel I am underprepared in the Maths side, and cannot travel internationally for Masters (financial + family reasons), so looking at Online options only at the moment.

Hi everyone, looking for some brutal honesty and guidance from the professionals here regarding my next career move.

My Background:

• Profile: 34M based in India.
• Education: Bachelors in Mechanical Engineering + a 1-year Diploma in Data Science.
• Experience: 4 years as a Data Analyst (heavy Python, SQL, Tableau, and advanced Excel).
• Current Situation: I took a career break starting in May 2024 due to health reasons and used this time to upskill and learn machine learning.\
• And due to this Career Break, I am having a tough time getting past preliminary HR calls and unable to land any interviews.

My Goal:

I want to pivot into Quant Risk, or FinTech, or Data Science/MLOps (bridging the gap between heavy data/tech and financial markets).

I am currently staring down two very different paths to end my career gap and make this pivot, and I don't want to waste the next 6-12 months on the wrong one.

Option A: The FRM Route

I start grinding for FRM Part 1. My plan would be to use Kaplan notes and supplement with some external probability/stats courses since my pure math background is decent but not at a "quant math major" level.

• My fear: I’ve heard the failure rate is brutal for non-finance folks, and I'm worried about sinking hundreds of hours into it only to fail.

Option B: The MSCS Route (Georgia Tech OMSCS)

I target an online MS in Computer Science (specifically GT OMSCS). To guarantee admission with my Mechanical Bachelors, I would spend the next few months taking accredited, graded prerequisite CS classes (like C++ and Data Structures) before applying, and then go all-in on the Master's.

• My fear: It's a longer academic commitment, though it directly builds the tech skills (Python, ML, Systems) needed for the roles I want.
• I can start applying for jobs as soon as I get in the Masters program.

My Questions for the Community:

1. If I take the FRM Part 1 with my proposed study stack (Kaplan + basic Probability & Statistics prep), what are the realistic chances of passing on the first attempt? Am I underestimating the math?
2. If I can't clear in the first attempt, would I be able to clear in the 2nd? Will the knowledge I gain from FRM 1 attempts be of any use? Help me land any jobs in case I can't clear the FRM 1?
3. In the Asian/Indian financial hubs, would a top-tier MSCS (like Georgia Tech) yield a higher ROI and better employer trust for my target roles than the FRM?
4. The preparation - c, c++, computer science knowledge I gain while preparing for GT OMSCS would help me in the long run, and if I am admitted into the Masters at GT, I feel i would land interviews and job opportunities and dont have to wait until the end of the program. Is my thinking correct?

I really appreciate any insights you all can provide.

P.S. I am unable to do Masters in Financial Engineering because at my current capabilities I feel I am underprepared in the Maths side, and cannot travel internationally for Masters (financial + family reasons), so looking at Online options only at the moment.