Associate, Investment Engineering & Analytics (12-month Contract)

CPP Investments | Investissements RPC•Toronto, ON

11d•Onsite

About The Position

We are seeking a highly motivated and detail-oriented Associate to join the Strategy Data, Investment Engineering & Analytics group under Capital Markets and Factor Investing. This role is responsible for enhancing investment team decision-making by integrating traditional and alternative data, research outputs, and advanced analytical methodologies into systematic factor investment models. The successful candidate will be empowered to take ownership of results and deliver end-to-end engineering solutions—from raw data ingestion to strategy implementation. The Investment Engineering & Analytics group works closely with research and portfolio management functions to support systematic investment strategies across equities, fixed income, currencies, commodities, options, etc. The group manages and enhances data, models, portfolio and risk analytics, ensuring scalability, accuracy, and efficiency. The successful candidate will operate across data, analytics, and workflow design—owning problems end-to-end and continuously refining solutions based on real-world usage and stakeholder feedback. This role will also focus on leveraging AI to accelerate development and enhance investment workflows.

Requirements

Bachelor’s degree in finance, engineering, computer science, mathematics, or a related field.
3-5 years of experience in a related role within finance or investment management.
Strong ability to solve complex problems through a combination of quantitative reasoning, analytical thinking, and programming expertise.
Demonstrated experience working with relational databases, with strong proficiency in SQL and Python.
Excellent communication and interpersonal skills.
Ability to work collaboratively in a fast-paced and dynamic environment.

Nice To Haves

Experience with PySpark, data science libraries (e.g., pandas, NumPy), and modern data engineering techniques is considered a strong asset.
Experience in systematic investing, research, portfolio analytics, or AI techniques is a plus.

Responsibilities

Build and maintain robust data pipelines with strong validation and monitoring for research and production environments.
Take end-to-end ownership of the data lifecycle, from data vendor due diligence and research data ingestion to production deployment and ongoing support of data-driven live strategies.
Partner with investment researchers to explore, analyze, and evaluate new traditional and alternative datasets, assessing structure, data quality, stability, and investment relevance.
Collaborate closely with quantitative researchers, portfolio managers, and investment engineers to develop data products and deliver robust data access layers that support systematic strategy implementation and portfolio analytics.
Contribute to the research and development of investment strategies, and drive continuous improvement in data architecture, quality, and operational robustness.
Leverage AI to accelerate development, enhance data quality monitoring, and improve overall efficiency.