Role Summary
You will spearhead the development, optimization, and deployment of cutting-edge algorithmic strategies and quantitative models. The position blends deep hands-on technical work with high-level strategic oversight across research, engineering, and trading operations.
Key Responsibilities
Quantitative Strategy Development & Research
- Algorithm Design: Lead the creation and refinement of proprietary trading algorithms rooted in the firm's market framework, leveraging advanced statistical and machine-learning techniques.
- Modeling & Simulation: Build forecasting, signal-generation, and risk models; run rigorous back-tests and simulations to validate performance.
- Data Analysis: Mine large, heterogeneous datasets (market microstructure, alternative data, etc.) for actionable insights.
- Innovation: Continuously evaluate emerging research (deep learning, reinforcement learning, agent-based modeling) to sharpen our edge.
Technical Infrastructure & Implementation
- System Architecture: Partner with engineering to design high-throughput trading systems that scale globally.
- Software Development: Oversee codebases in Python, and C++; enforce best practices for testing, CI/CD, and performance monitoring.
- Automation & Integration: Build end-to-end pipelines for data ingestion, model training, and live deployment; ensure seamless connection to execution venues and data feeds.
- Tech-Stack Stewardship: Select and integrate best-in-class analytics platforms, databases, and cloud resources.
Performance Analysis & Risk Management
- Metrics & Analytics: Define and track KPIs-alpha decay, slippage, Sharpe, drawdown, and latency-via real-time dashboards.
- Risk Controls: Embed robust risk models and dynamic hedging; enforce firm-wide limits and compliance requirements.
- Optimization: Iterate relentlessly-parameter sweeps, sensitivity analyses, and scenario tests to future-proof strategies.
Collaboration & Leadership
- Team Mentorship: Grow and mentor a multidisciplinary team of quants, data scientists, and engineers; cultivate a culture of experimentation and peer review.
- Documentation & Code Quality: Champion readable, well-tested, version-controlled code and transparent research notebooks.
Qualifications
- Education: B.S. or M.S. in a quantitative field such as Mathematics, Computer Science, Engineering, Statistics, or Physics.
- Experience: Minimum 2 years building and deploying profitable algorithmic strategies at a hedge fund, bank, or proprietary trading firm.
- Programming: Advanced expertise in at least one core language (Python, C++, or Java) and familiarity with Linux, Git, and CI workflows.
- Data Science: Deep knowledge of statistical modeling, and machine-learning frameworks (PyTorch, TensorFlow, scikit-learn).
- Systems: Proven skill in real-time data pipelines, distributed/cloud computing, and performance optimization.
- Language: Fluent English (written and spoken) is required.
- Soft Skills: Exceptional analytical rigor, clear communication, and the leadership mindset to help build a high-performance team from scratch. Deep and careful thinking but still able to progress and iterate quickly
What we offer
-A well-funded trading firm expanding into AI research and discovery - bring your best ideas and be rewarded for them.
-Real ownership and influence on roadmap, direction and products.
-Competitive base compensation with significant upside tied to results.
-A culture optimized for deep work, fast learning, and doing the right thing.
-Unique and successful first principles based approach to markets that we haven't heard anywhere else
Compensation $400k-1m + upside exposure
