PhD Quant Researcher at NK Securities Research

Gurugram, haryana, India -

Full Time

Start Date

Immediate

Expiry Date

31 Mar, 26

Salary

0.0

Posted On

31 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Research, Modeling, Machine Learning, AI, Python, Statistical Learning, Data Analysis, Deep Learning, C++, Probability, Statistics, Linear Algebra, Empirical Models, Large Datasets, Computational Experiments, Order-Book Dynamics, Market Microstructure

Industry

Financial Services

Description

Why This Role Exists NK Securities is building a research-driven trading platform where models, not opinions, drive decisions. We are hiring PhD-level researchers to work on pricing models, market microstructure, and machine-learning-driven alpha that directly impact live trading systems. This is not a sandbox role. Your work will move capital, trade markets, and be evaluated in production. If you enjoy: Turning theory into models that survive noisy, non-stationary data Seeing your research deployed and stress-tested in real markets Working end-to-end—from idea to impact ,this role is designed for you. What You’ll Work On You will operate as a research owner, not a support function. Research & Modeling Design pricing and fair-value models at short horizons Model order-book dynamics, liquidity, impact, and micro-price behavior Research alpha signals using statistical learning and ML/AI methods Develop models robust to regime shifts, feedback loops, and adversarial noise Machine Learning & AI Apply machine learning and modern AI techniques to high-frequency market data Explore deep learning, representation learning, and sequence models where justified Balance interpretability, robustness, and predictive power Build models that generalize—not just optimize backtests From Research to Production Run large-scale experiments and rigorous backtesting Define validation criteria, failure modes, and monitoring metrics Partner with engineers and traders to deploy models into live systems Continuously iterate based on real performance feedback Model Classes You’ll Encounter You don’t need to know everything—but you should be excited to learn and extend: Pricing & Microstructure Fair-value and micro-price models Order-flow and liquidity models Spread, impact, and short-horizon price dynamics Statistical Models Time-series and state-space models Volatility and correlation structures Signal decay and stability modeling ML / AI Models Feature-based ML for alpha discovery Representation learning for structured market data Deep learning models used selectively and critically Who We’re Looking For Education PhD (completed or near completion) in Mathematics, Statistics, Computer Science, Physics, Electrical Engineering, Operations Research, or related fields Strong research pedigree and demonstrated ability to solve open-ended problems Research Strength Deep understanding of probability, statistics, and linear algebra Ability to translate abstract ideas into testable, empirical models Comfort reasoning under uncertainty and imperfect data Evidence of original thinking (papers, thesis work, significant projects) Technical Skills Strong Python for research and experimentation Experience with ML / AI frameworks (e.g., PyTorch, TensorFlow) Comfort working with large datasets and computational experiments Exposure to C++ or performance-oriented systems is a plus, not a requirement

Responsibilities

You will operate as a research owner, designing pricing models and researching alpha signals that impact live trading systems. Your work will involve applying machine learning techniques to high-frequency market data and deploying models into production.