Safder Shakil is a multidisciplinary quantitative researcher and aspiring algorithmic trader with a
foundation in aerospace engineering, financial modeling, and machine learning. Currently
pursuing his M.Tech in Techno-Entrepreneurship at the Indian Institute of Technology,
Hyderabad, Safder is focused on the intersection of advanced mathematics, deep learning, and
capital markets.

He has previously served as a Quant Developer at Q-DITS, where he designed and backtested
systematic trading strategies—including factor-based models and time-series analysis—for
equities. His work integrates predictive analytics, volatility modeling, and reinforcement learning
to enhance trading performance and improve risk-adjusted returns.

Safder holds a B.Tech in Aerospace Engineering and has contributed academically as a faculty
instructor in mathematics and quantitative methods. His growing technical toolkit includes
Python, TensorFlow, NumPy, and financial APIs—skills he applies toward building robust
algorithmic frameworks and real-time data pipelines.

Representing a new generation of tech-savvy finance professionals, Safder bridges fintech
innovation with deep technical knowledge—bringing together data science, quantitative
research, and a forward-looking approach to investment strategy.