AI Data Scientist

Responsibilities

Generative AI Use Case Assessment Shaping

Collaborate with Business stakeholders and Business 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

Filter out misscoped or unfeasible requirements before AI engineering engagement ensuring clean and actionable handovers

Generative AI Solution Research Design

Partner with Generative AI engineers to research design and refine AI solutions that address business needs

Research on the latest Generative AI trends emerging technologies and market best practices Contribute to enhancement to enterprise level AI frameworks playbooks and standards Incorporate industry best practices into model design evaluation and solution iterative optimization

Analyze model and solution behaviors to identify limitations such as misinterpretations hallucinations edge case failures or inconsistent responses and collaborate with engineers to implement improvements

Stay informed on the latest Generative AI trends emerging technologies and market best practices contributing insights to guide iterative development and continuous enhancement of AI solutions

Business Validation Collaboration

Support Business Analysts and users during UAT for Generative AI solutions and advise business users on Generative AI solution behaviour and behaviour root cause

Work closely with Technology and AI Engineering teams to clarify issues validate fixes and ensure solutions meet business intent and evaluation criteria

Machine Learning Advanced Analytics

Design and develop analytical and machine learning models for automation insights and predictive use cases

Leverage enterprise machine learning platforms to build and deploy models effectively

Document model logic assumptions and limitations to support transparency governance and knowledge sharing

Qualifications

Bachelors or Masters degree in Data Science Computer Science Artificial Intelligence Engineering Statistics or a 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 validation and continuous improvement

Experience working in Agile delivery environments collaborating with product owners business analysts and technology teams