Machine Learning Trading Systems

James M. Carter

********@*****.*** ** South End Ave, Apt 404, New York, NY 10280 +1-312-***-**** SUMMARY

Senior-level Systematic Trading Strategist with 20+ years of experience designing, engineering, and deploying high-performance trading systems, with deep expertise in automated execution, core engine development, and systematic trading automation. Strong cross-asset background spanning equities, futures, fixed income, and crypto. Adept in Python-centric data architecture, with consistent collaboration across trading, quant research, and risk teams. Committed to delivering robust, scalable, and production- grade trading solutions. Ongoing application of machine learning in trading system optimization and research pipelines.

CORE COMPETENCIES

Core Trading Engine Development

Designed, deployed, and maintained high-performance core trading systems supporting real-time execution, pricing, and risk analytics across multiple asset classes.

Integrated execution logic with robust error handling and monitoring frameworks to ensure stability, transparency, and auditability in live production. Systematic Trade Automation:

Designed and deployed trade automation frameworks improving signal execution, rebalancing, and alpha capture.

Created modular automation tools that allow rapid deployment and adaptation of trading logic, increasing research agility and time-to-market.

Collaborative Research & Development

Partnered with traders, PMs, and quant researchers to translate strategy insights into executable code, aligning development with business goals.

Code Quality & Support:

Enforced code reviews and production support to uphold system integrity and minimize downtime. Python Data Stack Proficiency: Expert with Python, Pandas, NumPy, DuckDB, SQL, and PySpark for research and real-time pipelines.

Quantitative & Statistical Modeling: Strong foundation in time-series analysis, backtesting, and quantitative trading strategy validation.

Machine Learning in Trading: Researching ML for signal evaluation, feature engineering, and parameter tuning (ongoing study and certification).

EXPERIENCE

BITFARMS LTD., Brossard, Quebec

Quantitative Trading Consultant 11/2024 - 03/2025 Designed robust Python-based trade automation and data pipelines to support crypto strategy research. Built a lightweight trading engine to simulate and evaluate alpha signals in real time. Enabled seamless integration of historical and live data sources for strategy development and testing. ERGOTELES CAPITAL MANAGEMENT, New York, NY

Senior Quantitative Strategist - Systematic Trading Group 05/2019 - 06/2023 Engineered distributed trading infrastructure and backtesting frameworks using diverse technologies, with significant Python contributions.

Hands-on developer adept at crafting specialized Python tools to help drive research and improve the research-to-production strategy lifecycle.

Technically proficient analyst experienced in evaluating diverse data sets to identify meaningful edges within the equities, futures, and cryptocurrency markets. Developed and launched systematic trading strategies targeting U.S. ETFs and stock index futures, leveraging data-driven signals and robust execution frameworks to capitalize on short-term and directional market inefficiencies.

Automated trading strategies for directional and spread positions in Eurex interest rate futures. CREDIT SUISSE ASSET MANAGEMENT, New York, NY

Quantitative Strategy Developer - Quantitative Investment Strategies Group 04/2015 - 05/2019 Architect and lead developer of the desk's trade allocation engine, managing all QIS' daily portfolio management operations, with core implementation in Python. Aided in the research, development and implementation of momentum and mean reversion strategies in futures and equities, leveraging Python.

Extensive experience with the Python finance ecosystem (pandas, numpy, jupyter-notebook, matplotlib) for all aspects of trading and analytics.

Technology mentor/internal course instructor for teaching Python and Data Science techniques in trading/finance for Credit Suisse's analyst development and continuing education programs. CONSULTING RISK MANAGEMENT & ANALYTICS, New York, NY Quantitative Developer - Enso Financial Analytics, Bank of America, China Construction Bank 04/2012- 04/2015

Built Python-based risk tools and trade analytics systems for fixed income and derivatives desks. Supported live operations, including trade monitoring, data quality checks, and model tuning. Delivered scalable analytics pipelines supporting CVA/FVA modeling and real-time VAR. BARCLAYS CAPITAL, New York, NY

Team Technical Lead - Electronic Interest Rate Trading 01/2011 - 04/2012 Integrated new trading analytics and OTC interest rate models into core trading systems (Python). Enhanced strategy logic for SEF and swap market execution; supported automated platform enhancements.

Collaborated with legacy tool users (Excel, VBA) to ensure continuity and migration to scalable platforms.

RONIN CAPITAL, New York, NY

Trader / Quantitative Developer 10/2008 – 12/2011 Developed firm’s FIX-based trading infrastructure for index rebalancing across ARCA, BATS, ICE, CME, CBOT.

Built and traded systematic ETF strategies leveraging mean reversion and statistical arbitrage. Implemented both back-end engines and front-end dashboards for real-time trading control (Java, FIX). MERRILL LYNCH, New York, NY

Quantitative Developer – Quantitative Strategies & Automation Group 08/2003 – 08/2008 Engineered full-stack trading infrastructure for intraday alpha models and automated execution in the US equities and futures markets.

Designed risk tools for scenario analysis and desk-wide portfolio sensitivity reporting. Collaborated with prop desks to tune models for short-term execution and capacity control. ABN AMRO BANK, Chicago, IL

Trader – Short-Term Interest Rate Desk 05/1993 – 08/2003 Managed the bank's $5B in short-term interest rate book; hedged risk via swaps, caps, floors, and futures.

Developed Excel/VBA-based dashboards to streamline desk-wide rate risk analysis and trade decisions. EDUCATION

Purdue University

Bachelor of Science – Computer and Electrical Engineering CERTIFICATIONS

FINRA Series 7, Series 63

Stanford University – Advanced Machine Learning

New York Institute of Finance – Machine Learning in Trading & Finance

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