Quant Trading

About the Role

The role is built around real-time, data-driven decision-making, and as such, you will be working closely with cross-functional teams to design and implement high-throughput trading systems that scale globally. Your expertise in software development, data analysis, and technical infrastructure will be essential in driving the company's mission forward.

Deeter Investments is a founder-led proprietary trading firm that prizes curiosity, collaboration, and a bias for action. With a strong focus on innovation and a culture optimized for deep work, fast learning, and doing the right thing, this role offers a unique opportunity for quants to make a real impact.

What You Will Do

• Lead the creation and refinement of proprietary trading algorithms rooted in the firm's market framework, leveraging advanced statistical and machine-learning techniques.
• Build forecasting, signal-generation, and risk models, and run rigorous back-tests and simulations to validate performance.
• Mine large, heterogeneous datasets for actionable insights, and continuously evaluate emerging research to sharpen the company's edge.
• Partner with engineering to design high-throughput trading systems that scale globally, and oversee codebases in Python and C++.
• Build end-to-end pipelines for data ingestion, model training, and live deployment, and ensure seamless connection to execution venues and data feeds.
• Select and integrate best-in-class analytics platforms, databases, and cloud resources, and enforce best practices for testing, CI/CD, and performance monitoring.
• Define and track KPIs via real-time dashboards, and embed robust risk models and dynamic hedging to enforce firm-wide limits and compliance requirements.
• Iterate relentlessly on strategy optimization, parameter sweeps, sensitivity analyses, and scenario tests to future-proof strategies.
• Grow and mentor a multidisciplinary team of quants, data scientists, and engineers, and cultivate a culture of experimentation and peer review.

What We Are Looking For

• B.S. or M.S. in a quantitative field such as Mathematics, Computer Science, Engineering, Statistics, or Physics.
• Minimum 2 years of experience building and deploying profitable algorithmic strategies at a hedge fund, bank, or proprietary trading firm.
• Advanced expertise in at least one core language (Python, C++, or Java), and familiarity with Linux, Git, and CI workflows.
• Deep knowledge of statistical modeling, machine-learning frameworks (PyTorch, TensorFlow, scikit-learn), and real-time data pipelines.
• Proven skill in distributed/cloud computing, performance optimization, and data analysis.
• Fluent English (written and spoken) is required, and exceptional analytical rigor, clear communication, and leadership mindset are essential.

Nice to Have

• Experience with deep learning, reinforcement learning, and agent-based modeling.
• Familiarity with cloud-based services such as AWS or Google Cloud.
• Certification in a relevant field, such as the Chartered Financial Analyst (CFA) designation.

Benefits and Perks

• Competitive base compensation with significant upside tied to results.
• Real ownership and influence on roadmap, direction, and products.
• A culture optimized for deep work, fast learning, and doing the right thing.
• Unspecified benefits, including potential equity, PTO, health insurance, and remote stipend.
• The opportunity to work with a well-funded trading firm that is expanding into AI research and discovery.
• Access to cutting-edge technologies and a collaborative, dynamic work environment.

• Tip: Showcase your expertise in machine learning, statistical modeling, and software development to stand out as a candidate.
• Be prepared to discuss your experience with real-time data pipelines, distributed/cloud computing, and performance optimization.
• Highlight your ability to work in a fast-paced environment and drive innovation, and demonstrate your leadership skills and ability to mentor a team.
• Make sure to research the company and understand their mission, values, and culture before applying.
• Be prepared to provide examples of your work, including any relevant projects or coding examples, to demonstrate your skills and expertise.
• Consider reaching out to current or former employees to gain insight into the company culture and work environment.
• Be prepared to negotiate your salary and benefits, and consider factors such as equity, PTO, and health insurance when evaluating the offer.