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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.
Typical Background 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.
Key Responsibilities 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.
Preferred Experience & Capabilities 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.
Technical Skills Python (NumPy, Pandas, SciPy, statsmodels, scikit-learn) Time-series modeling and statistical analysis Optimization techniques Quantitative finance concepts Core Skills Mathematics Quantitative Research
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