Python Developer - QIS (Indexes)
Jay Analytix · Toronto, Ontario, Canada
IT Services and IT Consulting · 11-50 employees
About the role
Design and maintain Python-based platforms for index calculation, rebalancing, and the implementation of systematic investment strategies. Collaborate with quantitative researchers to translate strategies into production-grade code and optimize data pipelines.
What they look for
Requirements
Requires 8+ years of professional software development experience with strong expertise in Python and Quantitative Investment Strategies. A bachelor's degree in a quantitative field and proficiency with scientific libraries and SQL are essential.
Benefits
Full description
Python Developer – QIS (Indexes)
Location: Toronto, ON (Hybrid – 3 days onsite per week) Experience: Minimum 8+ years Employment Type: Full-Time / Contract (as applicable)
About the Role
We are seeking a seasoned Python Developer with strong experience in Quantitative Investment Strategies (QIS) and index products to join our Toronto-based team. In this role, you will design, build, and maintain the technology platforms that power index calculation, rebalancing, and QIS strategy implementation. You will work closely with quantitative researchers, index analysts, and product teams to translate systematic strategies into robust, production-grade code.
Key Responsibilities
- Design, develop, and maintain Python-based applications supporting QIS and index calculation, construction, rebalancing, and back-testing workflows
- Implement and productionize systematic/rules-based investment strategies (e.g., factor, volatility, carry, momentum, multi-asset strategies) in collaboration with quant researchers
- Build and optimize data pipelines for market data ingestion, cleansing, and validation across equities, fixed income, FX, commodities, and derivatives
- Develop tools for index performance attribution, corporate action handling, and daily index level production
- Ensure accuracy, auditability, and timeliness of index calculations and strategy outputs, including reconciliation and exception handling
- Write clean, well-tested, well-documented code following software engineering best practices (version control, CI/CD, code reviews, unit/integration testing)
- Improve performance and scalability of existing calculation engines and libraries
- Collaborate with cross-functional stakeholders (research, product, operations, risk) to gather requirements and deliver solutions
- Support production systems, troubleshoot issues, and participate in release and change management processes
- Mentor junior developers and contribute to team standards and technical direction
Required Qualifications
- 8+ years of professional software development experience, with strong hands-on expertise in Python
- Proven experience in Quantitative Investment Strategies (QIS), index development/calculation, or systematic trading environments
- Strong knowledge of financial markets and instruments — equities, futures, options, FX, fixed income — and index methodologies (rebalancing, weighting schemes, corporate actions)
- Proficiency with Python scientific/data libraries: pandas, NumPy, SciPy; experience with back-testing frameworks a strong plus
- Solid SQL skills and experience working with relational databases and large financial datasets
- Experience with market data vendors and platforms (e.g., Bloomberg, Refinitiv/LSEG, FactSet)
- Strong grasp of software engineering practices: Git, CI/CD pipelines, automated testing, code review, Agile delivery
- Excellent analytical and problem-solving skills with high attention to detail and data accuracy
- Strong communication skills and ability to work directly with quants, product, and business stakeholders
- Bachelor's degree in Computer Science, Engineering, Mathematics, Finance, or a related quantitative field
Nice to Have
- Master's degree or professional designation (CFA, FRM)
- Experience at an index provider, investment bank QIS desk, asset manager, or ETF issuer
- Exposure to cloud platforms (AWS, Azure, or GCP), containerization (Docker/Kubernetes), and workflow orchestration tools (e.g., Airflow)
- Experience with performance optimization (vectorization, multiprocessing, Cython) for large-scale calculations
- Familiarity with derivatives pricing, risk models, or portfolio optimization techniques
- Knowledge of regulatory considerations for benchmarks/indexes (e.g., IOSCO principles, BMR)
Why Join Us
- Work at the intersection of quantitative finance and technology on products used by institutional investors
- Hybrid work model based in downtown Toronto
- Collaborative environment with direct exposure to quant research and index product teams
- Competitive compensation and benefits package