Job Responsibilities:
Design, develop, maintain, and optimize in-house research data platforms (including price volume, fundamental, and alternative data), providing quantitative researchers with reliable, high-quality, and stable data sources and analysis tools.
Establish protocols for data injection, processing, quality assurance, anomaly detection and archiving, and streamline and improve processes.
Work with external partners to onboard new datasets, conduct domain-specific data analysis and data mining for new datasets, and collaborate with quant researchers to evaluate new data sources.
Develop and maintain quantitative research tools.
Qualifications:
Bachelor's degree or higher in computer science or a related technical area.
1-5 years of experience in programming for a professional setting.
Proficiency in the Python programming language and its scientific computing ecosystem (numpy, Pandas, Arrow, etc.) is preferred.
Familiarity with the state-of-the-art data engineering ecosystem is a plus.
Experience in processing financial data is a plus.
Experience in machine learning is a plus.
Knowledge of quantitative research and trading is a plus.
Being fast, rigorous and critical in thinking.
Effective communicator with a strong sense of teamwork.
Highly motivated and capable of thriving in a fast-paced environment.
Scientech Research Capital is a quantitative trading firm founded by wall street veterans each with 10+ years of proven track record from top-notch firms. SRC strives to leverage the innovations and breakthroughs in technology to discover fundamental values in the financial markets. We pride ourselves in adhering to scientific principles and nurturing creativity in quantitative research. As a proprietary trading firm, we utilize our own capital to deploy investments. Currently we have presence in major global exchanges with daily trading volume over $1B USD. Since the company founded in 2019, our trading strategy and infrastructure have weathered through the 2020 financial market storm, riding unseen volatility spike and handling massive data volume with ease. Our 50+ team combines deep academic expertise—STEM Ph.D.s from top institutions—with elite mathematical talent, including U.S. MOP/CMO/NOI gold medalists, and leading researchers in AI. We are actively seeking talents to build out our multi-asset trading and research platform, and extend the footprint to global markets.
