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Chandni_Bhatia
Chandni
Bhatia
VP and Lead Quantitative Developer
JP Morgan
United States

My background is in electrical engineering. What drew me towards quantitative finance was the realization that the mathematical and computational thinking I was developing as an engineer also mapped to quantitative financial problems, but with much higher real-world stakes. My first exposure to the quant world was at the Reserve Bank of India, where the experience of doing econometric research that fed into policy decision making at the national level showed me how risk management and quantitative work could be. From there I moved on to credit risk modeling at Credit Suisse, and then into quantitative development at Morgan Stanley. 

The CQF was particularly valuable because it gave me a formal, structured grounding in financial engineering concepts. I was already applying them in practice but hadn't learned about them systematically before. I was working in the quantitative field at that time and pursued the program alongside my credit modeling role at Credit Suisse, so I was able to connect what I was learning in the program to real problems immediately. It also gave me a professional credential, which is a good signal to employers that you are really interested in pursuing a career in quantitative finance, particularly at an institution or a European bank where it is recognized as an international standard. I think the CQF genuinely helped me accelerate my career. 

Two things stand out hen I consider which skills were most valuable from the CQF.

First is the rigorous treatment of moderate risk and validation. So, not just building models, but also stress testing them, challenging their assumptions, and documenting their essence for regulatory purposes. This has been directly applicable throughout my career and something that I learned during the CQF. Second would be the discipline of connecting theory to implementation. The CQF doesn't let you stay abstract; you are expected to apply those concepts. This habit of thinking is something I use every day. You have to come up with new ideas to implement a model at such a large scale at a global bank. 
 

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