Master's degree in Business (Economics, Marketing, Supply Chain Management etc.) or Data & AI field (Computer Science, Statistics, Artificial Intelligence, Machine Learning etc.). MBA is a plus
Bachelor’s degree in biological and chemical sciences or equivalent (Molecular Biology, Biotechnology, Chemistry, Chemical Engineering etc.)
2-4 years of corporate experience in a regional or global role in a global MNC / consulting experience from a leading management consultancy with experience in Data & AI
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Drive the industrialization of AI capabilities from proof of concept to production, ensuring reliability, performance, cost efficiency, and operational supportability.
Establish reusable patterns, accelerators, and platform services to enable faster adoption of AI use cases across business units.
Work with business stakeholders across distribution, operations, claims, underwriting, customer service, risk, and corporate functions to identify and prioritize AI and innovation opportunities.
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• Ideation and Design Leadership: Facilitate design thinking sessions and co-innovation workshops with clients to identify impactful AI opportunities across business domains.
• Architecture and Solution Design: Translate business and data needs into target-state AI architectures — covering model lifecycle, agentic systems design, and cloud-native AI platforms.
• Infrastructure and Capacity Planning: Design AI infra blueprints spanning data, compute, GPU/TPU capacity, observability, and security, ensuring optimal cost-performance balance and resilience.
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Assist in translating product requirements into working implementations with reduced handoff friction between frontend and backend
Act as a full stack "seed learner" within the team — absorb full stack practices, contribute ideas, and grow into an autonomously delivering full stack engineer
Observe cross-team collaboration processes and proactively suggest improvements to product, design, and engineering workflows
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Assist in translating product requirements into working implementations with reduced handoff friction between frontend and backend
Act as a full stack "seed learner" within the team — absorb full stack practices, contribute ideas, and grow into an autonomously delivering full stack engineer
Observe cross-team collaboration processes and proactively suggest improvements to product, design, and engineering workflows
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Act as a full stack "seed" within your team — champion full stack practices, mentor peers, and help scale AI-augmented development across the organization
Proactively identify efficiency bottlenecks in cross-team collaboration and propose improvements to product, design, and engineering processes
Contribute to the full product lifecycle — from ideation and design to deployment and iteration
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Deploy AI solutions in collaboration with diverse teams. Develop and support enterprise GenAI and LLM-powered applications.
Deliver innovative GenAI solutions with strong governance - robust monitoring for data and AI models. Ensure model reliability, data quality, and compliance.
Lead client engagements, deliver impactful technical solutions, and serve as a trusted advisor.
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Plan, supervise and perform (if necessary) the development of supervised and unsupervised machine learning tools to process information from various data sources, including commercial databases and alternative, non-traditional datasets.
Plan, supervise and perform (if necessary) the generation of impact measures using machine learning, in collaboration with the Institute’s Directors and other Research Fellows.
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