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

Toronto

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design and build end-to-end data workflows, from ingestion to deployment

  • Build Python-based automation to cut manual effort in workflows

  • Develop analytics, dashboards and reporting for portfolio and trading decisions

  • Support models used in portfolio construction, rebalancing and research

  • Analyze investment and operational data to find process efficiency gains

From the employer’s posting
Design, develop and implement end-to-end data workflows, including data ingestion, transformation, analytics and deployment.
Leverage AI-assisted development tools and Python-based automation to build scalable solutions, streamline workflows and reduce manual effort and operational complexity.
Develop and enhance data analytics, dashboards and reporting capabilities to support portfolio management, trading and investment decision-making.
Support the development and maintenance of models and analytics used in portfolio construction, rebalancing and investment research.
Analyze investment and operational data to identify opportunities for process optimization, automation and efficiency improvements.

What you’ll bring

All qualifications

Core experience

  • Bachelor's degree in finance, engineering, computer science, mathematics or an equivalent qualification.
  • 3–5 years of relevant experience in finance, investment management or a related field.
  • Proficiency in Python, with experience using data science libraries such as pandas or NumPy considered a strong asset.
  • Experience with data visualization and dashboarding tools such as Dash, Streamlit or QuickSight is preferred; familiarity with SQL and data querying is an asset.
  • Experience or interest in AI/ML techniques, prompt engineering or automation, combined with strong communication, collaboration and interpersonal skills; familiarity with project management principles is an asset.
Qualification wording
Bachelor's degree in finance, engineering, computer science, mathematics or an equivalent qualification.
3–5 years of relevant experience in finance, investment management or a related field.
Proficiency in Python, with experience using data science libraries such as pandas or NumPy considered a strong asset.
Experience with data visualization and dashboarding tools such as Dash, Streamlit or QuickSight is preferred; familiarity with SQL and data querying is an asset.
Experience or interest in AI/ML techniques, prompt engineering or automation, combined with strong communication, collaboration and interpersonal skills; familiarity with project management principles is an asset.

Tools in this posting

  • Python
  • SQL
  • NumPy
  • pandas
  • Streamlit
Source — Tool mentions in context
- Design, develop and implement end-to-end data workflows, including data ingestion, transformation, analytics and deployment. - Leverage AI-assisted development tools and Python-based automation to build scalable solutions, streamline workflows and reduce manual effort and operational complexity. - Develop and enhance data analytics, dashboards and reporting capabilities to support portfolio management, trading and investment decision-making.
- 3–5 years of relevant experience in finance, investment management or a related field. - Proficiency in Python, with experience using data science libraries such as pandas or NumPy considered a strong asset. - Strong analytical and problem-solving skills, with an interest in applying data-driven and AI-driven approaches to business and investment challenges.
- Exposure to market execution, financial products, portfolio analytics or Investment Book of Record (IBOR)/Murex considered an asset. - Experience with data visualization and dashboarding tools such as Dash, Streamlit or QuickSight is preferred; familiarity with SQL and data querying is an asset. - Experience or interest in AI/ML techniques, prompt engineering or automation, combined with strong communication, collaboration and interpersonal skills; familiarity with project management principles is an asset.

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 27, 2026 · 2 days ago
Recorded sightings
3
Last seen by us
Oct 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

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Job description

View original posting ↗

Purpose. Performance. People.


Joining CPP Investments means joining one of the world’s most admired and respected institutional investors to drive a single mandate: to deliver strong, sustainable returns for generations of Canadians.  

 

With a long-term horizon and global reach, we deploy capital at scale across public and private markets. Our size, stability, and disciplined investment philosophy allow us to pursue complex opportunities and build enduring partnerships worldwide. 

 

For our people, this means meaningful work with tangible impact, real opportunity, and collaboration with exceptional colleagues who value partnership and performance. Here, you’ll contribute to outcomes that matter alongside team members committed to excellence and shared success. 


The Role


As an Associate, Investment Engineering & Analytics, you will develop scalable data, analytics and AI-enabled solutions that support portfolio management, trading and investment decision-making within Total Fund Management (TFM).

As part of the Total Portfolio Investment Platforms team, you will collaborate across investment engineering and business teams to deliver end-to-end solutions, from data ingestion to production-ready analytics and reporting tools. You will help modernize investment processes, automate workflows and enhance operational efficiency while supporting initiatives related to data, analytics and market execution.



The Team


Total Fund Management (TFM) supports the management of the Fund's overall portfolio, including portfolio construction, rebalancing and investment activities that contribute to CPP Investments' long-term investment objectives.


Within TFM, the Total Portfolio Investment Platforms team develops and enhances the data, processes and models supporting portfolio management, rebalancing, trading and research. The team collaborates across the Fund to deliver strategic initiatives related to public market modernization, data, analytics and market execution, with a focus on scalable solutions, automation and AI-enabled capabilities.


Accountabilities

  • Design, develop and implement end-to-end data workflows, including data ingestion, transformation, analytics and deployment.
  • Leverage AI-assisted development tools and Python-based automation to build scalable solutions, streamline workflows and reduce manual effort and operational complexity.
  • Develop and enhance data analytics, dashboards and reporting capabilities to support portfolio management, trading and investment decision-making.
  • Support the development and maintenance of models and analytics used in portfolio construction, rebalancing and investment research.
  • Analyze investment and operational data to identify opportunities for process optimization, automation and efficiency improvements.
  • Collaborate with investment engineering teams and functional and strategic partners across the Fund to coordinate workflows, manage handoffs and deliver integrated solutions.
  • Contribute to project management and delivery within assigned teams, working with subject matter experts and business partners to advance new capabilities and continuously improve solutions.

What You Bring

  • Bachelor's degree in finance, engineering, computer science, mathematics or an equivalent qualification.
  • 3–5 years of relevant experience in finance, investment management or a related field.
  • Proficiency in Python, with experience using data science libraries such as pandas or NumPy considered a strong asset.
  • Strong analytical and problem-solving skills, with an interest in applying data-driven and AI-driven approaches to business and investment challenges.
  • Exposure to market execution, financial products, portfolio analytics or Investment Book of Record (IBOR)/Murex considered an asset.
  • Experience with data visualization and dashboarding tools such as Dash, Streamlit or QuickSight is preferred; familiarity with SQL and data querying is an asset.
  • Experience or interest in AI/ML techniques, prompt engineering or automation, combined with strong communication, collaboration and interpersonal skills; familiarity with project management principles is an asset.

You are motivated to contribute to something larger than yourself, approach complex challenges with rigor, and hold yourself to high standards in a collaborative, performance-driven environment. 


We provide colleagues with cutting-edge AI tools, dedicated learning time, and practical support to help them deliver with greater impact.

 

Inclusion & Accessibility

CPP Investments is committed to equitable access to employment and building a workforce that reflects diverse talent and perspectives. If you require accommodation at any stage of the recruitment process, please let us know and we will work with you to meet your needs. 

 

Attention: Protect Yourself from Fraud

CPP Investments is committed to a secure and transparent recruitment process. We will never ask candidates for payment or financial information at any stage of hiring. All legitimate opportunities are posted on our careers page, and communications will come from our applicant tracking system, Workday. 


CPP Investments may use AI tools to help screen and assess applicants by analyzing resumes and applications for relevant skills and experience. These tools support, but do not replace, human decision-making.


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Toronto

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