About the Company:

AlphaGrep is a quantitative trading and investment firm founded in 2010. We are one of the largest firms by trading volume on Indian exchanges and have significant market shares on several large global exchanges as well. We use a disciplined and systematic quantitative approach to identify factors that consistently generate alpha. These factors are then coupled with our proprietary ultra-low latency trading systems and robust risk management to develop trading strategies across asset classes (equities, commodities, currencies, fixed income) that trade on global exchanges.

1.1. Team Overview We are a new Quantitative Trading Team specializing in global equities and leveraging machine learning models to drive daily trading decisions. The team operates at the intersection of cutting-edge data science and real-time trading, using advanced ML signals to identify opportunities in equity markets every day. We are seeking Quantitative Researchers to join us in our Shanghai or Singapore office.

As a Quantitative Researcher on the team, you will play a key role in end-to-end research and trading operations. This is a generalist position involving everything from data preparation and model development to live trading system oversight. You will collaborate with other researchers and engineers to transform data into actionable trading signals, ensure the smooth running of our trading systems, and help monitor risks. This role is ideal for a highly motivated junior professional who wants to apply strong quantitative skills and learn the full cycle of systematic trading in a fast-paced, collaborative environment. Our team emphasizes a tight-knit, collaborative culture where autonomy and initiative are highly valued and rewarded. 

1.2. Key Responsibilities

• Data Mining & Preprocessing: Onboard, clean, and post-process diverse datasets from internal databases and external vendors. Ensure data quality and readiness for research, including handling financial data, and other data sources.

• Production Monitoring: Oversee the daily operation of automated trading systems in global equity markets. Monitor live trading performance and system health, promptly troubleshoot issues to ensure high reliability and uptime reliability during market hours.

• Machine Learning Model Development: Research, train, and refine machine learning models for predicting market behavior and generating trading signals. Perform feature engineering, algorithm experimentation, and backtesting to improve model performance and robustness.

• Risk Monitoring & Reporting: Monitor real-time portfolio exposure and risk metrics. Generate regular reports on strategy performance and risk indicators, and alert the team to any anomalies or breaches of risk limits. Work with senior team members to ensure trading strategies adhere to the firm’s risk management standards.

1.3. Qualifications & Skills

• Education: Degree in Mathematics, Physics, Computer Science, Machine Learning, Financial Engineering, or another quantitative discipline. Strong academic performance (high GPA) from a top-tier university is expected. A PhD in a relevant field is a strong plus.

• Programming: Proficiency in Python is required, with the ability to write efficient code for data analysis and modeling. Experience with scientific computing and machine learning libraries (pandas, xgboost, pytorch, NumPy, etc.) is highly desirable. Familiarity with Q/KDB+ (time-series databases and the Q language) is a strong plus.

• Machine Learning: Exposure to machine learning techniques or data science projects (through coursework, research, or internships) is an advantage. A demonstrated interest in applying ML to real-world problems, especially in finance, will be valued.

• Quantitative & Analytical Skills: Solid foundation in mathematics and statistics, with excellent problem-solving abilities. Comfort with analyzing large datasets and applying statistical methods to derive insights is important. • Communication: Effective and professional communication skills. Ability to collaborate in a team and convey ideas clearly. Good written English is essential.

• Attention to Detail: Detail-oriented and reliable, capable of monitoring complex systems and ensuring data and results are accurate. Responsive and alert during critical market hours.

• Experience Level: Open to early-career professionals and recent graduates. Experience in quantitative research, data analysis, or related fields is appropriate. Relevant internship (e.g. in finance or tech) or PhD thesis is a plus. A strong willingness to learn and contribute is critical.

• Additional Plus: Enthusiasm for financial markets and systematic trading. A genuine interest in global equity and data-driven decision-making will help you excel. 

• Personal Attributes: o High degree of autonomy and initiative o Team-oriented mindset and strong collaborative skills o Commitment to delivering impact work that will be actively recognized and rewarded o Enthusiastic about working on the cutiting edge of technology and solving complex problems.

1.4. Start Date • Ideally in June 2025 • Only full time applicants will be considered

Why You Should Join Us:

• Great People. We’re curious engineers, mathematicians, statisticians and like to have fun while achieving our goals.
• Transparent Structure. Our employees know that we value their ideas and contributions.
• Relaxed Environment. We have a flat organisational structure with frequent activities for all employees such as yearly off-sites, happy hours, corporate sports teams, etc.
• Health & Wellness Programs. We believe that a balanced employee is more productive. A stocked kitchen, gym membership and generous vacation package are just some of the perks that we offer our employees.