CHEManager International · 7 hours ago
Senior Quantitative Researcher - Market Microstructure
United States
Full-time
Remote
Senior Level
$155K/yr - $155K/yr
5+ years expSwish Analytics is a sports analytics startup focused on predictive sports analytics data products. The Senior Quantitative Researcher will own research and production pipelines for trading strategies, lead research initiatives, and collaborate with the Trading desk to translate quantitative insights into profitable strategies while ensuring risk management.
Responsibilities
Own end-to-end research and production pipelines for a strategy
Lead alpha research initiatives leveraging advanced statistical and machine learning techniques
Process and analyze high-frequency tick data, order book snapshots, and market microstructure signals with sub-millisecond latency requirements
Analyze price formation, market liquidity dynamics, and limit order book imbalances across electronic venues
Build and run Monte Carlo simulations to estimate P&L distributions, risk exposures, and portfolio dynamics
Develop, backtest, and optimize quantitative trading strategies with rigorous statistical validation
Interpret complex model outputs and communicate alpha generation mechanisms to portfolio managers
Write modular, clean, and efficient Python code; build custom analytics libraries and research frameworks
Lead design reviews and establish data quality and research reproducibility standards
Guide 1-2 junior researchers through project delivery and model development
Proactively engage with traders and infrastructure teams to clarify research objectives and resolve data dependencies
Design and implement transaction cost analysis (TCA) frameworks to measure and improve execution quality
Build market impact models and optimal execution strategies to minimize slippage across venue types
Develop real-time monitoring systems for latency, adverse selection, and execution performance metrics
Partner with infrastructure teams on ultra-low-latency data feeds and smart order routing algorithms
Qualification
Required
Master's degree in a quantitative discipline (Mathematics, Statistics, Physics, Computer Science, Financial Engineering) strongly preferred; PhD a plus
Expert-level Python skills; able to build production-grade research and trading systems
Strong SQL skills; experience with complex queries on tick databases and time-series datasets
Deep experience with Monte Carlo methods, stochastic calculus, and probabilistic modeling
Proven ability to develop, backtest, and deploy systematic trading strategies with demonstrable P&L
Experience processing high-frequency tick data and real-time market feeds
Familiarity with AWS or similar cloud infrastructure for large-scale backtesting and research
Track record of mentoring junior quantitative researchers
Excellent communication skills; ability to present complex quantitative research to portfolio managers and trading desks
Deep understanding of equity/futures market microstructure, order types, and matching engine logic
Experience building sophisticated TCA frameworks with market impact decomposition
Familiarity with FPGA or kernel-bypass networking for latency-critical applications
5-8 years of experience in quantitative research, systematic trading, or statistical modeling
Preferred
Proficiency in Rust, C++, or other systems languages for performance-critical components
Experience with MLOps, model monitoring, and adaptive retraining pipelines for regime detection
Background in derivatives pricing, options market making, or volatility arbitrage
Familiarity with FIX protocol, Betfair or Matchbook API experience, and ultra-low-latency trading infrastructure
Company
CHEManager International
Wiley’s leading media brand providing first-hand information on the global chemical, life science and process industries
201-500 employees
Funding
Current Stage
Growth StageCompany data provided by crunchbase