Sr Data Scientist, AI/ML

Key Responsibilities

• Design, develop, and deploy AI and machine learning solutions aligned to strategic business objectives and enterprise AI initiatives.
• Execute key components of the Model Development Life Cycle (MDLC), including data exploration, feature engineering, model development, validation, deployment, and performance monitoring.
• Build and optimize predictive models using traditional machine learning and advanced AI techniques.
• Support development of agentic AI solutions that automate business processes while incorporating governance, safety guardrails, and human-in-the-loop controls.
• Design and implement LLM-powered applications utilizing Retrieval-Augmented Generation (RAG), vector databases, embeddings, prompt orchestration, and evaluation frameworks.
• Develop and refine AI agents that improve workflow automation, decision support, and business productivity.
• Partner with AI Engineers to integrate AI capabilities into enterprise applications, APIs, and workflow platforms.
• Build lightweight prototypes and user-facing applications using tools such as Streamlit to accelerate solution validation and adoption.
• Develop and deploy AI solutions leveraging cloud platforms including AWS and GCP.
• Utilize modern data platforms such as Snowflake and Databricks to support scalable AI and analytics workloads.
• Collaborate with MLOps and engineering teams to implement CI/CD, monitoring, testing, and governance best practices.
• Ensure AI solutions are secure, scalable, reliable, and aligned with enterprise architecture standards.
• Partner with business leaders, product managers, engineers, and data teams to identify opportunities for AI-driven value creation.
• Translate complex analytical findings into actionable business recommendations.
• Communicate technical concepts, trade-offs, and outcomes effectively to both technical and non-technical stakeholders.
• Stay current on emerging AI technologies, industry trends, and best practices while contributing thought leadership across the organization.

Required Qualifications

• Master's degree or higher in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative discipline.
• 5+ years of experience applying Data Science, Machine Learning, and AI techniques to real-world business problems.
• Strong programming skills in Python and SQL.
• Experience with machine learning model development, validation, deployment, and monitoring.
• Experience with cloud platforms such as AWS and/or GCP, including AI/ML services.
• Experience working with modern data platforms such as Snowflake and Databricks.
• Working knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector stores, and agentic AI frameworks.
• Strong understanding of machine learning concepts including supervised learning, unsupervised learning, feature engineering, cross-validation, model evaluation, and optimization.
• Familiarity with software engineering best practices including Git, testing, logging, and version control.
• Excellent communication, collaboration, and stakeholder management skills.

Preferred Qualifications

• Experience building and deploying production-grade Generative AI and Agentic AI solutions.
• Experience mentoring junior data scientists and technical team members.
• Experience within financial services, insurance, wealth management, or consumer finance environments.
• Familiarity with model governance, responsible AI frameworks, and enterprise AI controls.
• Experience building AI-powered workflow applications and business-facing tools.