Equities Alpha Quant Researcher - Alternative Investment Firm
NYC based
They are seeking an experienced quant alpha researcher(s) to be key member(s) of the team. Primary duties
for Senior QRs include:
· Be a hands-on leader and innovator in one (or more) of the research areas: statistical alpha,
fundamental alpha, advanced statistical (machine) learning methods, and portfolio construction.
· Actively participate in the team's research agenda creation & review. Work proactively with
other team members to identify new directions of research, new data sources, and/or new
strategies.
· Responsible for the full research life cycle of each research project, from idea generation, model
design, signal testing to pre-production implementation.
· Mentor junior teammates; provide research and technical training as well as career guidance.
Requirements:
· Minimum 3 years (preferably 5+ years) of buy-side experience in the fields of statistic arbitrage
research and/or quantamental research. Experiences in building alpha models from intraday to
daily, weekly, or monthly horizons will all be considered.
· Prior experiences as quant PM or sub-PM with live track record a strong plus, but not required.
· Experience in designing and building a large-scale high throughput research and backtest platform
will be highly valued.
· Firm conviction and clear understanding of a disciplined and well-defined research process is
essential.
· Deep knowledge and experiences with various quant data sets and vendors.
· Strong python programming skills required, with extensive hands-on experience with various
scientific computing and machine learning packages.
· Academic and professional experiences in applying modern ML techniques and tools to quant
finance a strong plus.
· Experience with any of the following languages a plus: SQL, Java, C++ and Matlab.
· Good communication skills and strong leadership skills, willing and capable of working teammates
with various levels of experiences.
· M.S. or above in Math, Statistics, CS, Physics, Computer Engineering, Financial
Engineering/Computational Finance, or similar fields required, with strong background in mathematics and statistics. PhD in relevant fields and academic research background will be highly valued.
