Overview
Quantitative Analyst Jobs in Bangalore, Karnataka, India at William O’Neil India
Job Summary:
As part of the Quantitative research and trading team, the candidate will be responsible for developing and backtesting trading strategies on Indian and International markets. The candidate will work closely with the investment management team of portfolio managers and other researchers to identify profitable ideas and work closely with developers to product ionize these ideas for live trading.
Duties & Responsibilities:
Analyze financial time series data to identify profitable trading opportunities
Develop new and improve existing trading strategies using properitary platforms
Apply machine learning and statistical analysis methods to get insights from fundamental and other unstructured data.
Work closely with our data science and investment management teams to provide research insights.
Assit the team in developing new analytical tools and processes
Competencies:
Ability to work independently and in a
collaborative team
environment.
Effectively communicate (and listen) clearly, professionally, politely and persuasively in all situations; respond well and in a reasonable, timely manner.
Challenge conventional practices and use creativity and information to lead, innovate, problem solve, and implement ideas to contribute to the growth of the organization.
Take personal responsibility for productivity, quality and timeliness of work.
Qualifications & Requirements:
Bachelor’s/Master’s degree in Engineering, Statistics, Mathematics or other quantitative discipline
3-5 years of experience working in quantitative research role, developing mid/low frequency trading strategies
Strong programming skills with proficiency in Python
Strong knowledge of data structures, algorithms, databases like SQL
Experience handling large datasets is preferred
Experience in machine learning and Artificial Intelligence is preferred
Title: Quantitative Analyst
Company: William O’Neil India
Location: Bangalore, Karnataka, India
Category: Finance & Banking (Data Scientist)
