QSentia ยท 7 hours ago
Quantitative Researcher
United States
Part-time
Remote
Senior Level
5+ years expQSentia is building a next-generation hedge fund platform that integrates reinforcement learning with large language models. As a Senior Quantitative Developer, you will design and implement a proprietary framework for Alpha Generation and Risk Management, combining quantitative finance expertise with advanced machine learning and software engineering.
Financial Services
Hiring Manager
Aditi Dewan
Responsibilities
Design and implement RL-based portfolio optimization models (e.g., DDPG, TD3, PPO) with a focus on adaptive risk management and regime detection
Develop and integrate LLM-driven alpha signals, enabling the system to extract hidden insights from multimodal data sources (earnings calls, filings, news, social sentiment, market structure)
Architect a scalable pipeline that combines real-time alpha vectors with RL-driven portfolio allocation and trade execution
Build and maintain walk-forward and event-driven backtesting frameworks with realistic transaction cost and slippage models
Implement multi-metric validation frameworks beyond Sharpe/Sortino, including max drawdown, Calmar, CVaR, and risk-concentration metrics
Collaborate with researchers and portfolio managers to translate quantitative research into production-grade trading systems
Optimize performance for GPU-accelerated training and efficient data pipelines (SQL, cloud, or hybrid)
Qualification
Required
5+ years of experience in quantitative development, algorithmic trading, or applied ML research in finance
Strong background in machine learning / reinforcement learning (PyTorch, TensorFlow) applied to portfolio management or trading strategies
Experience designing actor-critic RL frameworks (DDPG, TD3, PPO, SAC) with risk-adjusted reward functions
Deep understanding of financial markets, risk models, and portfolio theory
Proficiency in Python (NumPy, Pandas, PyTorch) and SQL/NoSQL databases; C++ or Rust is a plus
Hands-on experience with LLMs (OpenAI, Claude, Gemini, etc.), natural language processing, or multimodal AI for financial signal extraction
Proven ability to design backtesting engines and eliminate lookahead bias with point-in-time datasets
Strong communication skills and ability to work with PMs, researchers, and technologists
Preferred
Experience with real-time market data APIs (Polygon, Bloomberg, Refinitiv, etc.)
Knowledge of options markets and derivatives pricing
Familiarity with distributed computing frameworks (Ray, Dask, Spark) for large-scale research
Prior experience at a hedge fund, HFT shop, or asset manager in a quant dev or quant research role
Benefits
Equity + points in fund with the potential for salary and bonus post funding.
Company
QSentia
Initial back test results: Sharpe: 2.6 Calmer: 5.6 Sortino: 5.5 Max DD: +18%
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase