This role is for one of the Weekday's clients

Salary range: Rs 2000000 - Rs 4000000 (ie INR 20-40 LPA)

Min Experience: 2 years

Location: Bangalore, India

JobType: full-time

The Quantitative Research Engineer will design, develop, and evaluate data-driven trading strategies using rigorous mathematical and statistical techniques. This role is ideal for candidates with a strong quantitative background who are highly proficient in Python and experienced in translating research ideas into scalable, testable code.

• Degree in Mathematics, Statistics, Physics, Operations Research, or Computer Science with a strong mathematical foundation.
• 2–4 years of experience in quantitative research, algorithmic trading, or data science roles.
• Deep understanding of probability theory, time-series analysis, optimization, and statistical modeling.

• Develop, implement, and backtest systematic trading strategies using Python.
• Work extensively with large-scale financial datasets including order-book data, tick-level data, and time-series features.
• Apply statistical and quantitative models to identify trading signals and evaluate performance.
• Convert research concepts and models into clean, modular, and testable production-ready code.
• Collaborate with engineering and trading teams to support model deployment and optimization.

• Hands-on experience building and backtesting strategies such as statistical arbitrage, mean reversion, and momentum-based models.
• Practical implementation of time-series models including Kalman Filters, GARCH, and related techniques using Python.
• Strong coding discipline with version control; GitHub or similar repositories showcasing well-documented research notebooks or backtesting frameworks are highly valued.

• Python (NumPy, Pandas, SciPy, statsmodels, scikit-learn)
• Time-series modeling and statistical analysis
• Optimization techniques
• Quantitative finance concepts

Mathematics
Quantitative Research