QSentia ยท 2 hours ago
Quantitative Researcher I
United States
Part-time
Remote
Mid, Senior Level
1+ years expQSentia is building a next-generation hedge fund platform that integrates reinforcement learning with large language models to enhance portfolio management. The Senior Quantitative Developer will design and implement advanced models and frameworks for alpha generation and risk management, leveraging machine learning and software engineering expertise.
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
1+ 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
Founder 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