AI Data Scientist

Job Details: 

Responsibilities

1 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 infeasible requirements before AI engineering engagement ensuring clean and actionable handovers

2 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 enterpriselevel 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 edgecase 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

3 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

4 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

1 Bachelors or Masters degree in Data Science Computer Science Artificial Intelligence Engineering Statistics or a related quantitative discipline

2 3-7 years of applied experience in AI machine learning analytics and Generative AI roles

3 Handson experience with Generative AI solutions eg chatbots copilots LLMbased tools agentic assistants in enterprise environments

4 Strong understanding of the endtoend AI lifecycle including use case definition feasibility assessment evaluation validation and continuous improvement

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

Preferred Skills

1 Generative AI Expertise Deep understanding of Generative AI models model behaviour and limitations and application frameworks with the ability to assess solutions and guide improvements

2 AI Solution Design Ability to translate business pain points into actionable AI opportunities and propose solutions that balance speedtomarket cost and quality

3 Cloud Microsoft AI Stack Familiarity with cloudbased AI platforms preferably within the Microsoft ecosystem eg Azure Copilot Studio AI Foundry with awareness of cloud and data constraints in GenAI solution design

4 Agile Delivery Collaboration Experience supporting iterative delivery UAT cycles and sprintbased refinement with Business BAs and Technology teams

5 Banking Enterprise Context Understanding of banking products operating models and regulatory considerations with the ability to assess GenAI use cases in a regulated enterprise environment

6 Communication Stakeholder Engagement Strong ability to clearly convey AI capabilities risks and recommendations to both technical and nontechnical stakeholders