Jobs at Geneva Trading

Staff Accountant responsible for daily trading income reconciliations, firm and trader P&L reporting, global financial close processes, audits, tax activities, business funding support, and process improvement projects. The role requires advanced Excel skills, accounting or business education, analytical ability, and collaboration in a fast-paced financial services environment. Preferred experience includes regulatory reporting, dashboard tools, NetSuite, financial markets or cryptocurrency, relational databases, and two or more years in financial services or fintech.

Paid 10-week Python software engineering internship on a DevOps team. Responsibilities include developing Python scripts, optimizing tooling, supporting CI/CD, collaborating with senior technologists, deploying solutions, and exploring AI-driven automation for log analysis, anomaly detection, and alerting in a trading infrastructure environment.

Provides part-time, on-site IT and desktop support for employees in a trading environment. Responsibilities include troubleshooting hardware, software, Microsoft Office, phones, printers, and enterprise AI tools; configuring workstations and applications; managing user accounts; and maintaining IT inventory. The intern will receive mentorship while applying classroom knowledge and learning help desk, hardware, networking, and AI-assisted troubleshooting skills.

Supports change releases, deployments, troubleshooting, monitoring, log analysis, and issue escalation for trading systems. Develops scripts to automate tasks and uses generative AI and LLMs to improve troubleshooting, log analysis, anomaly detection, and proactive monitoring. This 10-week paid internship includes mentorship, training, and project work supporting a systems reliability engineering team.

Ten-week paid software engineering internship developing, testing, and deploying C++ solutions for a proprietary trading platform. Interns work with large datasets, network programming, multithreaded applications, AI coding tools, and cross-functional technologists and researchers. The role includes mentorship, complex problem-solving, collaboration, and opportunities for full-time employment after graduation.

Build data pipelines and relational data models using Python and SQL; clean operational data, support scenario analysis, and create dashboards for PMO leadership. Explore LLMs and machine learning for text analysis and data-quality automation. Gain production experience with testing, documentation, maintainable code, and data-driven decision support in a trading environment.

Trade futures in a proprietary trading environment while receiving structured mentorship and hands-on training. Responsibilities include identifying and researching market opportunities, applying systematic and data-driven trading strategies, managing an individual trading account, contributing market insights, and collaborating with technology teams to use and improve electronic trading systems. The role requires discipline, precision, emotional control, perseverance, and comfort working under pressure.

The Quant Trader will manage trading positions, analyze data for opportunities, enhance trading tools, and collaborate with teams to solve complex problems in a trading environment.

As a Discretionary Trader, you will leverage advanced technology to scale profitable strategies and identify new opportunities, collaborating with a tech team to enhance trading systems.

Design, build, and maintain internal front-end trading tools, dashboards, and supporting APIs. Partner with traders, Risk, and Technology to gather requirements, improve performance, reliability, and scalability, and provide production support for real-time, high-throughput trading systems.

Lead the OTC Oil Desk, managing a team of traders, developing trading strategies, and ensuring adherence to risk management and regulatory standards.

As an Experienced Discretionary Trader, utilize innovative technology to scale profitable strategies, identify new opportunities, and collaborate with a technology team.

Lead a small data engineering team and own market data platforms from ingestion through delivery. Build and maintain KDB+/Q time-series systems, ensure data correctness, low-latency decoding, replay/recovery, and reliable distribution to downstream consumers. Write production code, review designs, improve observability, and prepare the platform for AI-driven consumers.