Requirements
Requires a Master's or PhD in a quantitative discipline (Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science) and 6+ years of experience in software development and technical leadership. Must have proven hands-on experience developing and deploying AI/ML solutions in production, leading large-scale transformation projects, and influencing senior stakeholders. Proficiency in Python, Java, or C++ and AI/ML frameworks (TensorFlow, PyTorch, Agent Development) is essential, along with a deep understanding of machine learning, deep learning, NLP, computer vision, and predictive analytics. Experience with cloud platforms (AWS, Azure, GCP), MLOps, and distributed systems is required, as are strong communication, analytical, problem-solving, and strategic thinking skills, with demonstrated ability to lead and mentor teams.
Description
As an AI Transformation Lead in Asset & Wealth Management, you will drive the strategy and execution of cutting-edge AI initiatives, collaborating with talented teams to solve complex business challenges. You will have an opportunity to make a significant impact, foster innovation, and help build a data-driven culture. Join us and be at the forefront of AI advancement, where your expertise will empower teams and transform the way we work. As an AI Transformation Lead in our Technology & Data team, you will architect and execute our enterprise-wide AI strategy, translating business needs into scalable, AI-driven solutions. You will collaborate with executive leadership and cross-functional teams to deliver impactful results, foster a culture of innovation, and ensure best practices in AI governance. Your leadership will be key in driving change, mentoring teams, and positioning us as a leader in AI adoption.
Job Responsibilities
- Develop and implement a comprehensive AI transformation roadmap aligned with organizational goals.
- Architect, design, and deploy scalable, secure AI/ML infrastructures and application stacks. Build prototypes, optimize data pipelines, and develop APIs/microservices for AI integration.
- Collaborate with senior stakeholders, data scientists, product managers, and engineering teams to define requirements and ensure seamless AI integration.
- Evaluate and implement emerging AI tools and methodologies to maintain technological leadership.
- Champion change management and develop learning paths to upskill teams in AI literacy.
- Define and track KPIs to measure the success and ROI of AI initiatives, reporting to executive leadership.
- Establish and enforce standards for data quality, model governance, security, privacy, and ethical AI practices.
Required Qualifications, Capabilities, and Skills
- Master’s or PhD degree in quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science
- 6+ years of experience in software development and technical leadership roles.
- Proven hands-on experience developing and deploying AI/ML solutions in production environments and demonstrated experience leading large-scale transformation projects and influencing senior stakeholders.
- Proficiency in programming languages such as Python, Java, or C++ and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Agent Development).
- Deep understanding of machine learning, deep learning, NLP, computer vision, and predictive analytics. Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods
- Experience with cloud platforms (AWS, Azure, GCP), MLOps pipelines, and distributed systems.
- Exceptional communication skills, able to articulate complex technical concepts to non-technical audiences. Strong analytical, problem-solving, and strategic thinking and demonstrated ability to lead and mentor cross-functional teams in a fast-paced environment.
Preferred Qualifications, Capabilities, and Skills
- Prior experience in enterprise AI transformation or digital modernization initiatives.
- Familiarity with data governance, security, and ethical AI frameworks.
- Experience with agile methodologies and change management.
- Track record of driving AI adoption and upskilling teams.
- Published research or patents in AI/ML fields.