Quant Researcher - EPAT Content Team

Job Description

Role Summary: QI seeks to hire suitable candidates to be a part of the EPAT Content team. About the team and its role in QI: The EPAT Content team has former bankers, programmers, and academics who worked in financial firms, universities, and tech companies. We have educational backgrounds in engineering, electronics, economics, and finance. The common thread stringing all of us is an obsessive curiosity to learn more about quantitative finance. We are responsible for the technical content and maintaining the quality of lectures delivered by top professionals worldwide in the EPAT (a six-month course conducted over weekends. You can check more about the course elsewhere on the website). We want to hear from you if you're interested in and excited to be part of a growing firm. Responsibilities: - Create content and conduct lectures, courses, and workshops for financial and educational institutions in India and abroad - Assist in the resolution of doubts and queries faced by students in lectures on quant finance - Enhance the content and delivery (pedagogy) of existing lectures - Write technical blogs on different aspects of quant trading - Supervise/evaluate the assignments and issues faced by course participants - Resolve queries on topics about statistics, machine learning, econometrics, Python, and other facets of quant trading - Contribute to research in the domain via writing and reviewing articles, manuscripts, and books connected to quant finance Qualifications and other aspects (The points in italics are prerequisites. Please do not apply if you don't satisfy them.) - 4-6 years of full-time work experience (industry experience is necessary) - Completed a Doctorate or Master's in engineering, statistics, computer science, finance, or other quantitative fields from a reputed university - Experience in knowledge delivery would be highly preferred - Expertise in the data science stack of at least one of Python and R (Python preferred) - Good grasp of math, statistics, and machine learning (in the context of financial markets) - Excellent writing, and speaking skills - Extensive knowledge of trading in the financial markets - Knowledge of financial instruments across asset classes - Ability to learn and digest new technical ideas/tools and implement them - Ability to work on multiple tasks and prioritize - Work over some weekends to take lectures or provide assistance to faculty during EPAT lectures (You will be eligible for compensatory offs that can be availed during weekdays)