Company Description Make an impact at a global and dynamic investment organization
- Stimulating work in a fast-paced and intellectually challenging environment
- Accelerated exposure and responsibility
- Global career development opportunities
- Diverse and inspiring colleagues and approachable leaders
- A hybrid-flexible work environment with an emphasis on in-person collaboration
- A culture rooted in principles of integrity, partnership, and high performance
- An organization with an important social purpose that positively impacts lives
Job Description
Team Description
Accountabilities
- Design and implement technology solutions to automate post-investment credit monitoring processes, such as financial modeling, covenant tracking, risk analytics, and reporting workflows.
- Collaborate with credit professionals to understand business needs, translate requirements into technical specifications, and build robust, user-friendly tools.
- Work in project-based teams to generate ideas, prototype, test, and refine new applications from concept to production.
- Build and deploy intelligent agents using machine learning or GenAI to enhance automation and early-warning capabilities across the credit portfolio.
- Develop and maintain scalable data pipelines to ingest, transform, and store structured and unstructured credit data from internal and external sources.
- Ensure system reliability, maintainability, and integration with CI's broader technology and data infrastructure, including collaboration with the Tech \& Data group and external vendors.
Qualifications
- 3-6 years of experience in software development, data engineering, or quantitative analysis, preferably within a financial services or fintech context.
- Proficiency in one or more programming languages such as Python, SQL, or JavaScript; experience with ETL tools, APIs, and data modeling is highly desirable.
- Experience building production-ready systems that solve real-world business problems, preferably in an investment, risk, or operations setting.
- Experience or interest in credit markets, financial analysis, and private investing.
- Demonstrated ability to work collaboratively in cross-functional teams, with strong communication skills and comfort working with non-technical stakeholders.
- Familiarity with GenAI, LLMs, or machine learning applications is considered a strong asset.
- Undergraduate or graduate degree in Computer Science, Engineering, Data Science, Mathematics, or a related field.
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