S&C Global Network - AI - Financial Services Analytics -Risk Analytics- Senior Manager

About S&C - Global Network: -

• Data & AI practice help our clients grow their business in entirely new ways.

• insights that inform better decisions and strengthen customer relationships.

• from accessing and reporting on data to predictive modelling
• to outperform the competition.

What’s in it for you?

They develop specialized expertise—strategic, industry, functional, technical—in a diverse project environment that offers multiple opportunities for career growth.

• For large transformation deals, design robust data and AI strategy by discovering right business use cases and reinventing process design.
• Define strategies to assess clients' current data and apply AI capabilities, developing roadmaps for the future using tools such as data diagnostics, data and AI maturity assessment, and business case development.
• Bring expertise to define and execute data and AI platform strategies for stakeholders, covering areas such as cloud computing, emerging data and AI platforms/ technologies/ trends, and ecosystem strategies.
• Design architecture and operating model blueprints including organizational design, delivery engagement models, and talent & learning roadmaps that enable seamless integration and scalability of AI solutions across the organization, ensuring alignment with business goals and technical requirements.
• Develop strategic roadmaps for the implementation of AI initiatives, outlining key milestones, dependencies, and timelines to ensure successful execution and alignment with business priorities.
• Provide thought leadership on emerging data and AI trends, patterns, and technologies, shaping proofs of capability and enabling clients to harness and adopt innovation in the data and AI domain.
• Collaborate with cross-functional teams to build compelling business cases for AI initiatives, conducting thorough cost-benefit analyses, ROI assessments, and risk evaluations to support decision-making and investment prioritization.
• Infuse Responsible AI in the core AI foundation and solution design, develop plan for leveraging ecosystem partners, and define operating model to foster a culture of innovation and experimentation.