Commodities Systematic Trading - Associate (Mumbai)

J.P. Morgan is seeking a Trader support to join our Commodities Systematic Trading team. The candidate will be embedded in our cross market systematic effort which touches portion of alpha generation, e-trading, and data science and machine learning. This Developer will work as part of our teams in Mumbai, with a focus on commodities markets. The individual must be responsible, independent, driven and able to work in smooth coordination with a global team, with an aim to spearhead a local team. The environment is fast-paced, dynamic and highly collaborative within a globally distributed group. Role responsibilities: Build and maintain tools, UIs and frameworks supporting our systematic risk taking in our commodities trading businesses. Build and maintain systematic strategies and performance monitoring and attribution systems. Enhance the robustness and integration of the tools and models within the wider asset class efforts. Process, clean and analyse large datasets used in the context of alpha research. Work closely with traders to learn, understand and improve relevant tools and models. Required qualifications, capabilities and skills: Extensive professional experience in software development, with a strong focus on Python Experience with data analysis techniques along with relevant data science libraries (numpy, pandas, etc.) and visualization tools (dash, panel) Knowledge of database systems (KDB) Strong interpersonal and communication skills; ability to collaborate effectively with traders, quantitative researchers and software developers Exceptional attention to detail and outstanding work ethic Bachelor’s or Master’s degree in Computer Science, Computer Engineering or a related field Preferred qualifications, capabilities and skills: Knowledge of futures (commodities a plus) and how Experience with systematic / quant research at any velocity (high, medium, low). Proficiency in Python. Experience working collaboratively on common codebases using git Experience in data cleaning, processing, and migration.