AI Data Scientist

1w1 week ago

Capgemini

Kuala Lumpur, MY · Full-time · MYR 180,000 – MYR 300,000

About this role

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like. You’ll be supported and inspired by a collaborative community of colleagues around the world. Join us to help leading organizations unlock the value of technology.

Collaborate with business stakeholders and analysts to identify, define, and prioritize Generative AI opportunities. Conduct frontend feasibility and scope assessments, evaluating use case suitability, data readiness, risk, and value potential. Filter out misscoped or unfeasible requirements before AI engineering engagement.

Partner with Generative AI engineers to research, design, and refine solutions addressing business needs. Work closely with technology and AI teams to clarify issues and ensure solutions meet business intent. Help business analysts and users during UAT, advising on solution behavior and root causes.

Research latest Generative AI trends, emerging technologies, and market best practices. Contribute to enterprise AI frameworks, playbooks, and standards. Design and develop machine learning models using enterprise platforms for automation and insights.

Requirements

Bachelor's or Master's degree in Data Science, Computer Science, Artificial Intelligence, Engineering, Statistics, or related quantitative discipline
3-7 years of applied experience in AI, machine learning, analytics, and Generative AI roles
Hands-on experience with Generative AI solutions e.g. chatbots, copilots, LLM-based tools, agentic assistants in enterprise environments
Strong understanding of the end-to-end AI lifecycle including use case definition, feasibility assessment, evaluation, and continuous improvement
Experience working in Agile delivery environments collaborating with product owners, business analysts, and technology teams
Deep understanding of Generative AI models, behavior, limitations, and application frameworks
Familiarity with cloud-based AI platforms preferably Microsoft ecosystem e.g. Azure Copilot Studio, AI Foundry
Understanding of banking products and operating context

Responsibilities

Collaborate with business stakeholders and analysts to identify, define, and prioritize Generative AI opportunities
Conduct frontend feasibility and scope assessments evaluating use case suitability, data readiness, risk considerations, and value potential
Partner with Generative AI engineers to research, design, and refine AI solutions addressing business needs
Analyze model and solution behaviors to identify limitations like hallucinations or edge case failures and implement improvements
Help business analysts and users during UAT for Generative AI solutions and advise on behavior root causes
Work closely with technology and AI engineering teams to clarify issues and formalize fixes
Design and develop machine learning models for automation, insights, and use cases
Leverage enterprise machine learning platforms to build and deploy models effectively

Benefits

Empowered to shape your career in the way you’d like
Supported and inspired by a collaborative community of colleagues around the world
Reimagine what’s possible and unlock the value of technology
Help build a more sustainable, more inclusive world