Description
Requisition ID: 209353
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
We are seeking a highly skilled and analytical AI Quantitative Investment Analyst to join our AI Quant Group. As a AI Quantitative Investment Analyst, you will be responsible for researching, identifying and recommending leading AI technology for the purpose of integrating AI and machine learning into our investment strategies with the end objective of driving superior investment performance.
You’d be the ideal candidate if you have a strong background in Artificial Intelligence / Computer Science and a deep understanding of AI and its potential application to the investment process. You will have a strong understanding of financial markets and possess a passion for leveraging AI to uncover insights and the ability to assess potential innovative tools for optimizing investment processes and decision making.
This position will bolster our Credit Research team by bringing advanced AI expertise and experience within the team.
Is this role right for you? In this role, you will:
- Understand the SGAM investing environment and identify emerging AI tools that support quantitative investing including data analysis, pattern recognition and predictive modelling.
- Evaluate AI tools for opportunities and compatibility with existing quantitative investment strategies.
- collaborate with investment team portfolio managers to align AI tools with investment models and decision-making processes.
- identify opportunities where AI can improve alpha generation, portfolio optimization and investment risk management.
- lead or be an active participant in pilot projects to evaluate the effectiveness of AI tools in both test and live investment environments.
- remain current on AI trends, technology evolution, and regulatory developments.
- liaise with investment teams in AI strategy, information sharing, and opportunity identification to apply AI technologies to current investment processes.
Do you have the skills that will enable you to succeed in this role? We’d love to work with you if you have:
• Undergraduate or Master’s degree in Computer Science/AI, Data science, Mathematics or related field
• CFA, MBA or related designation is an asset.
• Minimum of 3 – 5 years of experience in investment analysis with a focus on AI or technology assisted investing.
• Strong understanding of AI, machine learning technologies and trends
• Understanding of cloud based AI services and their applicability in quantitative finance.
• Strong analytical and quantitative skills.
• Experience in communicating actionable trade ideas in a timely matter in fast moving markets.
• Skilled in financial software and tools (e.g., Bloomberg, Excel, Python).
• Excellent written and verbal communication skills.
• Demonstrated decision making, strategic influencing and leadership skills.
• Ability to work collaboratively in a team environment.
Location(s): Canada : Ontario : Toronto
Scotiabank is a leading bank in the Americas. Guided by our purpose: “for every future”, we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.
