Vice President - Data Science

As a Senior Data Scientist specializing in generative AI and fraud detection, your role will involve leading the design and implementation of generative AI use cases from ideation to production. You will be responsible for building and tuning LLM-based applications using platforms like Vertex, GPT, Hugging Face, etc. Additionally, you will create robust prompt engineering strategies and reusable prompt templates while integrating generative AI with enterprise applications using APIs, knowledge graphs, vector databases, and orchestration tools. Collaboration with Tech and business teams to identify opportunities and build solutions will be a key aspect of your role. Your key responsibilities will include: - Leading the design and implementation of generative AI use cases - Building and tuning LLM-based applications - Creating robust prompt engineering strategies and reusable prompt templates - Integrating generative AI with enterprise applications - Collaborating with Tech and business teams - Model development, validation, and testing of fraud detection models - Ensuring compliance with regulatory requirements and industry best practices - Documenting model development documents for MRM approvals and governance purposes - Staying current on GenAI trends, frameworks, and research - Mentoring junior team members and promoting a culture of experimentation and learning - Staying abreast of advancements in Gen AI, LLMs, and fraud prevention technologies Qualifications required for this role: - 11+ years of hands-on experience in data science or AI/ML roles - 7+ years' experience in statistical analysis with working knowledge of Python, Hive, Spark, SAS - 2+ years of hands-on experience specifically with generative AI or LLMs - Strong understanding of statistical concepts and modelling techniques - Strong programming skills in Python and familiarity with libraries like Transformers, PyTorch, or TensorFlow - Working knowledge of retrieval-augmented generation pipelines and vector databases - Understanding of MLOps, model evaluation, prompt tuning, and deployment pipelines - Experience building applications with OpenAI, Anthropic Claude, Google Gemini, or open-source LLMs - Familiarity with regulatory requirements and guidelines related to risk model validation - Strong communication skills and the ability to partner with both technical and non-technical stakeholders As a Senior Data Scientist specializing in generative AI and fraud detection, your role will involve leading the design and implementation of generative AI use cases from ideation to production. You will be responsible for building and tuning LLM-based applications using platforms like Vertex, GPT, Hugging Face, etc. Additionally, you will create robust prompt engineering strategies and reusable prompt templates while integrating generative AI with enterprise applications using APIs, knowledge graphs, vector databases, and orchestration tools. Collaboration with Tech and business teams to identify opportunities and build solutions will be a key aspect of your role. Your key responsibilities will include: - Leading the design and implementation of generative AI use cases - Building and tuning LLM-based applications - Creating robust prompt engineering strategies and reusable prompt templates - Integrating generative AI with enterprise applications - Collaborating with Tech and business teams - Model development, validation, and testing of fraud detection models - Ensuring compliance with regulatory requirements and industry best practices - Documenting model development documents for MRM approvals and governance purposes - Staying current on GenAI trends, frameworks, and research - Mentoring junior team members and promoting a culture of experimentation and learning - Staying abreast of advancements in Gen AI, LLMs, and fraud prevention technologies Qualifications required for this role: - 11+ years of hands-on experience in data science or AI/ML roles - 7+ years' experience in statistical analysis with working knowledge of Python, Hive, Spark, SAS - 2+ years of hands-on experience specifically with generative AI or LLMs - Strong understanding of statistical concepts and modelling techniques - Strong programming skills in Python and familiarity with libraries like Transformers, PyTorch, or TensorFlow - Working knowledge of retrieval-augmented generation pipelines and vector databases - Understanding of MLOps, model evaluation, prompt tuning, and deployment pipelines - Experience building applications with OpenAI, Anthropic Claude, Google Gemini, or open-source LLMs - Familiarity with regulatory requirements and guidelines related to risk model validation - Strong communication skills and the ability to partner with both technical and non-technical stakeholders