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Entry-level quant roles attract many strong candidates in metro locations with broad technical requirements.
Quant research skills are finance-specific and require domain knowledge, making cross-industry transfer limited.
Strict academic cutoffs (CGPA 8.5+, no backlogs) and strong technical requirements make selection stringent.
Develop and validate quantitative models and predictive signals for systematic trading strategies.
Conduct rigorous hypothesis-driven research on market behavior using large datasets and advanced statistical/machine learning techniques.
Collaborate with technologists to translate research into production systems impacting live trading and measurable PnL.
Bachelor's degree in Mathematics, Computer Science, Electrical Engineering, or another highly analytical field.
Minimum CGPA of 8.5 required; no active backlogs.
Strong programming skills in Python and/or C++.
Strong fundamentals in probability, statistics, linear algebra, and optimization; experience with machine learning or statistical modeling required.
Recent or upcoming graduate (2027) with demonstrated ability to handle ambiguous quantitative problems and large datasets.
Comfortable designing experiments and validating signals with intellectual rigor and statistical discipline.
Strong analytical mindset focused on uncovering novel trading edges rather than relying on existing frameworks or prior finance experience.