Quantitative Developer
Position OverviewA trading technology team is seeking a Quant Developer to engineer production systems for quantitative trading strategies, fair value models, and signal generation. This is an engineering-focused quantitative role responsible for converting trading research and strategy concepts into reliable, performant code used in live market environments. The role will partner closely with trading, engineering, and senior technical stakeholders on strategy implementation, model calibration, and analytics infrastructure.Mandatory Requirements:Must have 4+ years of software engineering experience.Must have strong Python development skills.Must have experience shipping production-quality code.Must have a strong quantitative foundation, including probability, statistics, basic machine learning, and numerical methods.Must be comfortable working with large datasets and analytical workflows.Must have experience with SQL, Pandas, and Snowflake or similar data warehouse technologies.Must be comfortable working in an AI-augmented development workflow, including directing, reviewing, and validating AI-generated code.Must have strong attention to numerical accuracy and production risk in trading or similarly sensitive systems.Must have strong communication skills and the ability to work closely with traders, engineers, and senior stakeholders.Key ResponsibilitiesBuild, maintain, and improve production implementations of trading strategies, fair value models, and signal generation systems.Develop quantitative analytics infrastructure, including markout analysis, fill quality measurement, regime detection, performance attribution, and net edge calibration.Enhance pricing and feature engineering pipelines, including integration of external sports odds data for sports-market fair value modeling.Contribute to the design and development of a next-generation strategy framework, including dry-run testing, parameter controls, and configuration audit trails.Build and support backtesting and replay systems that enable rapid strategy research, validation, and iteration.Use AI coding tools to accelerate development while applying rigorous review standards appropriate for production trading systems.Translate trading ideas into clear technical requirements, test cases, and deployable implementations.Improve observability for strategy execution, with attention to failure modes specific to quantitative trading systems.Partner with trading and engineering teams to ensure models, signals, and systems are accurate, reliable, and maintainable.Required QualificationsBachelor’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative discipline.4+ years of software engineering experience.Strong Python programming skills and a proven record of delivering production software.Solid mathematical background, including probability, statistics, introductory machine learning, and numerical methods.Ability to read technical papers, research notes, or specifications and translate them into working software.Experience with large-scale data analysis and analytical development workflows.Hands-on experience with SQL, Pandas, Snowflake, or comparable warehousing and data analysis tools.Ability to work effectively with AI-assisted development tools while carefully validating generated code.Strong focus on numerical correctness, edge cases, and risk controls.Defensive engineering mindset, especially around subtle defects that can affect trading outcomes.Excellent communication skills and ability to collaborate with trading, engineering, and business stakeholders.Intellectual curiosity, adaptability, and willingness to work across strategy, analytics, and infrastructure concerns.Preferred QualificationsExperience at a proprietary trading firm, hedge fund, market maker, or similar trading-focused environment.Experience with market-making, liquidity provision, quoting systems, inventory management, or spread capture economics.Experience with prediction markets, sports betting markets, event contracts, or similar market structures.Experience with dbt, dimensional modeling, or analytical data engineering.Experience building or maintaining strategy backtesting frameworks.Experience with replay-based validation or simulation environments.Familiarity with trading analytics such as markout distributions, regime detection, fill quality analysis, and P&L attribution.Why Join This Team / Organization SummaryThis role offers the opportunity to build production quantitative trading systems that connect research, analytics, and live strategy execution. It is well suited for an engineer with strong quantitative instincts who enjoys solving trading problems, working with complex data, and applying modern development workflows in a high-accountability environment.