Associate Director, Equities Quantitative Dev/Strat - New York, NY

About the role

This role contributes to the success of our Systematic and Quantitative Equities business, and the overall Equities Sales and Trading in Canada and US, by designing, developing, and implementing advanced models, trading strategies, and technology solutions, while ensuring individual goals, plans, and initiatives are executed & delivered in support of the team’s overall objectives.

Responsibilities

• Model Development: Design, implement, and improve pricing, hedging, and execution algorithms using Mathematical, Statistical/Machine Learning, and other Probability-driven models. Identify and resolve complex technical issues related to trading systems, ensuring high system performance and reliability.
• Data Analysis & Insights: Analyze large datasets (market, client behavior) to identify patterns and generate actionable insights. Simulate pricing and hedging models against historical data.
• Quant Development: Productionalize (ie. code) trading strategies and models, ensuring their speed and efficiency. Maintain and enhance production-level systems with robust testing and documentation.
• Data Engineering: Design, build and improve scalable, real-time data pipelines and APIs. Enhance business metrics, data quality / validation, and visualization.
• Collaboration: Partner with Sales, Trading, and Technology teams to deliver integrated solutions and improve platform capabilities. Establish consistent interaction with the voice trading desk and cultivate awareness of market trends and liquidity.
• Compliance, Risk, and Governance: Ensure adherence to regulatory requirements (SEC, FCA, IIROC) and internal policies on Compliance, Surveillance, and Risk across regions.
• Stay updated with the latest trends and advancements in quantitative finance, electronic trading, and programming techniques, including emerging technologies (cloud computing, GPU acceleration, AI/ML) and market microstructure research. Explore emerging techniques in Machine Learning & AI.
• Champions a customer focused culture to deepen client relationships and leverage broader Bank relationships, systems and knowledge.
• Champions a high-performance environment and contributes to an inclusive work environment.
• Actively pursues effective and efficient operations of his/her respective areas in accordance with Scotiabank’s Values, its Code of Conduct and the Global Sales Principles, while ensuring the adequacy, adherence to and effectiveness of day-to-day business controls to meet obligations with respect to operational, compliance, AML/ATF/sanctions and conduct risk.

Requirements

Required: Bachelor’s in Computer Science, Engineering, Mathematics, Physics, or related field.

Preferred: Advanced degree (M.Sc. or Ph.D.) in a quantitative discipline.

Preferred: 5+ Years experience in systematic equities with exposure to execution analysis, alpha research, and/or market-making. Preferred: Experience supporting a live trading book.

Technical Skills: Proficiency in Python, Java (C++ also acceptable), and strong object-oriented design principles. Familiarity with functional programming paradigms is also preferred. Experience with data manipulation (SQL) and numerical libraries (Pandas, NumPy). KDB/Q experience is a plus. Plus: Familiarity with electronic trading protocols, connectivity, routing (FIX, API integration). Plus: Knowledge of cloud computing, GPU acceleration, and distributed systems is an asset.

Quantitative & Analytical Skills: Solid foundation in probability and statistics. Plus: Experience with Machine Learning frameworks (GBTs, NNs, LLMs, etc.). Ability to design and validate models under real-world constraints.

Soft Skills: Effective communication skills to explain complex concepts to diverse stakeholders. Ability to work across time zones and adapt to regional market hours. Collaborative mindset and willingness to mentor junior team members.