Head of Quant Trading

Deeter Analytics; United States; On-site; USD 100,000 - 150,000; Full time

Benefits offered by this job

Competitive base compensation

Real ownership and influence on products

Unique approach to markets

Job summary

Deeter Analytics is seeking a Head of Quant Trading to lead the development and optimization of algorithmic trading strategies. You will oversee the implementation of high-throughput trading systems and mentor a team of quants and data scientists.

Applicants should possess a degree in a quantitative field and have at least 2 years of experience in profitable strategy deployment. The firm offers competitive compensation and a culture of deep work and innovation.

Qualifications

• Minimum 2 years building and deploying profitable algorithmic strategies.
• Fluent English (written and spoken) is required.
• Experience with statistical modeling and machine learning frameworks.

Responsibilities

• Lead the development of proprietary trading algorithms.
• Oversee codebases in Python and C++.
• Define and track performance KPIs via dashboards.

Skills

Statistical modeling

Machine learning

Algorithmic strategies

Risk management

Education

B.S. or M.S. in a quantitative field

Tools

Python

C++

Git

Linux

Job description

Deeter Investments is a founder‑led proprietary well funded trading firm built around real‑time, data‑driven decision‑making. 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 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

• 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; run rigorous back‑tests and simulations to validate performance.
• Continuously evaluate emerging research (deep learning, reinforcement learning, agent‑based modeling) to sharpen our edge.

Technical Infrastructure & Implementation

• Partner with engineering to design high‑throughput trading systems that scale globally.
• Oversee codebases in Python, and C++; enforce best practices for testing, CI/CD, and performance monitoring.
• Build end‑to‑end pipelines for data ingestion, model training, and live deployment; ensure seamless connection to execution venues and data feeds.
• Select and integrate best‑in‑class analytics platforms, databases, and cloud resources.

Performance Analysis & Risk Management

• Define and track KPIs (alpha decay, slippage, Sharpe, drawdown, and latency) via real‑time dashboards.
• Embed robust risk models and dynamic hedging; enforce firm‑wide limits and compliance requirements.
• Iterate relentlessly: parameter sweeps, sensitivity analyses, and scenario tests to future‑proof strategies.
• Grow and mentor a multidisciplinary team of quants, data scientists, and engineers; cultivate a culture of experimentation and peer review.
• 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.