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-endfrom 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 generalizenot 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 everythingbut 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
