Quant Trading
About Deeter InvestmentsDeeter Investments is a founderled proprietary well funded trading firm built around realtime, datadriven decisionmaking. We prize curiosity, collaboration, and a bias for action. After years of discretionary success, we think we have some unique ways of seeing the market and developing alpha for the future that have high odds of success. We're launching a dedicated algorithmic division-and we're looking for a Head of Quant Trading to architect and scale this effort from day one. Role SummaryYou will spearhead the development, optimization, and deployment of cuttingedge algorithmic strategies and quantitative models. The position blends deep handson technical work with highlevel strategic oversight across research, engineering, and trading operations.Key ResponsibilitiesQuantitative Strategy Development & ResearchAlgorithm Design: Lead the creation and refinement of proprietary trading algorithms rooted in the firm's market framework, leveraging advanced statistical and machinelearning techniques.Modeling & Simulation: Build forecasting, signalgeneration, and risk models; run rigorous backtests 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, agentbased modeling) to sharpen our edge.Technical Infrastructure & ImplementationSystem Architecture: Partner with engineering to design highthroughput 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 endtoend pipelines for data ingestion, model training, and live deployment; ensure seamless connection to execution venues and data feeds.TechStack Stewardship: Select and integrate bestinclass analytics platforms, databases, and cloud resources.Performance Analysis & Risk ManagementMetrics & Analytics: Define and track KPIs-alpha decay, slippage, Sharpe, drawdown, and latency-via realtime dashboards.Risk Controls: Embed robust risk models and dynamic hedging; enforce firmwide limits and compliance requirements.Optimization: Iterate relentlessly-parameter sweeps, sensitivity analyses, and scenario tests to futureproof strategies.Collaboration & LeadershipTeam 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, welltested, versioncontrolled code and transparent research notebooks.QualificationsEducation: 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 machinelearning frameworks (PyTorch, TensorFlow, scikitlearn).Systems: Proven skill in realtime 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 highperformance team from scratch. Deep and careful thinking but still able to progress and iterate quicklyWhat 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 elseCompensation $400k-1m + upside exposure