Jobs at DV Trading

Develop and operate back-office systems supporting trading, risk management, accounting, and settlements. Responsibilities include real-time and batch data processing, database schema design, daily reporting, job monitoring, trade-data flow management, and production reliability. The role requires advanced Python, PostgreSQL, workflow orchestration, CI/CD, testing, incident response, and communication with non-engineering teams. Preferred experience includes futures and options trade lifecycles, reconciliation, FIX and SFTP ingestion, DevOps/SRE practices, legacy modernization, and AI automation.

Own and evolve an on-prem Kubernetes platform supporting trading systems. Responsibilities include cluster lifecycle management, observability with metrics, logs, and traces, GitOps and CI/CD infrastructure, infrastructure automation, and self-service tooling. The engineer will onboard trading and development teams, build documentation and runbooks, troubleshoot Linux systems, and scale reliable platform services across the firm.

Build and productionize quantitative trading tools, energy-market models, analytics, data pipelines, and visualization tools. Collaborate with traders, quants, and engineers to develop signal research, backtesting, risk and pricing integrations, and time-series data infrastructure. Monitor, test, document, and iteratively improve production models and tools based on trader feedback.

Build and productionize quantitative trading tools, energy-market models, analytics, dashboards, and data pipelines. Collaborate with traders, quants, and engineers on signal research, backtesting, risk and pricing integrations, time-series data storage, visualization, monitoring, testing, and documentation. The role requires strong Python and quantitative skills, experience with financial or commodities data, and familiarity with modern data and software engineering tools.

Supports day-to-day trading operations across multiple asset classes, including trade capture, reconciliation, pricing, settlements, PnL reporting, monitoring, and position management. Designs alerts and data integrity checks, collaborates with developers on databases and trading tools, and streamlines onboarding processes for traders, strategies, and products. Requires strong analytical, organizational, communication, and problem-solving skills in a fast-paced environment.

Build and improve proprietary trading tools for commodity trading desks. Collaborate with developers, technology leaders, traders, and researchers to define technical needs and deliver platform functionality. Design greenfield solutions, extend existing codebases, and use AI tools while maintaining ownership of code quality, verification, deployment, and production support. The role is onsite five days per week in London.

Support database health, performance, availability, maintenance, troubleshooting, access management, documentation, SQL optimization, automation, migrations, replication, and disaster recovery testing. Collaborate with engineers and analysts while learning database performance tuning and operational best practices.

Build and operate full-stack, real-time risk applications supporting PnL, VaR, greeks, dashboards, alerts, and analytical tools. Own deployment, CI/CD, infrastructure, monitoring, incident response, reliability, and performance. Develop Python backend systems, responsive JavaScript interfaces, database integrations, and LLM-powered workflows. Collaborate with risk developers, quantitative analysts, and market risk analysts to implement financial models and production-ready applications.

Build and maintain scalable data pipelines supporting trading, research, and risk systems. Responsibilities include ingesting, cleaning, validating, enriching, storing, and optimizing large-scale market data; monitoring pipeline health; troubleshooting issues; integrating pipelines with trading infrastructure; and documenting data flows and schemas. The role collaborates closely with quantitative researchers, traders, and software engineers in a fast-paced financial markets environment.

Conduct market-data research to identify predictive signals, build and backtest quantitative models, apply statistical and machine-learning methods, maintain high-frequency data pipelines, collaborate with traders, and monitor live strategy performance. The role focuses on systematic signal generation across multiple time horizons for equities and futures market-making.

Monitor and manage trading platforms across multiple markets, support Linux trading environments, troubleshoot order event streams using logs and packet captures, and provide technical support to traders. Collaborate with development, trading, and IT teams to onboard opportunities, improve trading infrastructure, automate processes, and drive strategic operational initiatives.

Manage institutional client relationships across Greater China and APAC for ETFs, equities, and listed derivatives. Quote, negotiate, and execute OTC and RFQ orders with trading desks; oversee client onboarding, documentation, connectivity, and account setup; provide pre- and post-trade analysis; communicate market flow to trading and research; maintain relationships with issuers, exchanges, venues, and brokers; and ensure accurate booking and regulatory compliance.

Manage prime brokerage, clearing, FCM, local broker, and sub-custody relationships across APAC. Responsibilities include provider selection, commercial negotiations, onboarding, connectivity coordination, performance monitoring, regulatory tracking, and troubleshooting settlement or allocation issues. The role requires expertise in margin, financing, stock loan, futures clearing, market access, and APAC-specific account structures and regulations.

Chief of Staff supporting DV Equities’ Asia-Pacific market-making desk by managing planning, reporting, leadership cadence, cross-functional projects, recruiting coordination, budgets, vendors, regulatory initiatives, and operational issue resolution. The role partners with trading, technology, operations, risk, compliance, legal, finance, and HR, and requires strong financial understanding, stakeholder management, communication, discretion, and English and Mandarin fluency.

Conduct quantitative research for equities trading by analyzing market data, identifying predictive signals, building and backtesting statistical and machine learning models, developing data pipelines, deploying production strategies, and monitoring live performance. Collaborate with researchers and traders across global offices to translate research findings into trading decisions.

Research systematic trading signals across multiple time horizons by analyzing market data, building and backtesting quantitative models, applying statistical and machine learning methods, and maintaining data pipelines. Collaborate with traders and senior researchers to translate findings into robust trading strategies and improve research prototypes based on simulation results.

Software Developer Intern supporting an equities trading desk during the 2027 summer internship. Responsibilities include developing low-latency C++ trading components, building Python tools for data analysis and backtesting, optimizing code, participating in code reviews, and collaborating with traders, quantitative researchers, and developers. The role offers hands-on exposure to algorithmic trading technology and requires strong programming skills, knowledge of data structures and algorithms, and familiarity with Linux and networking.

Build and backtest quantitative trading models, analyze high-frequency market data for predictive signals, monitor trading positions and risk, and collaborate with traders, researchers, and developers on systematic strategies. The intern will also improve daily trading processes, resolve position and P&L discrepancies, identify market opportunities, and present research findings and recommendations.

Summer 2027 software development internship on an equities trading desk. The intern will develop low-latency C++ trading components, build Python tools for data analysis and backtesting, optimize existing code, participate in code reviews, and collaborate with traders, quantitative researchers, and developers. The role requires strong C++ or Python skills, understanding of algorithms and data structures, Linux/Unix familiarity, and interest in algorithmic trading.

Conduct quantitative research on equities market data by identifying predictive signals, building and backtesting statistical and machine learning models, and translating findings into trading strategies. The intern will work with traders and senior researchers, maintain large-scale market data pipelines, and refine research prototypes using backtest results and feedback.