• Lead and manage the data science team, fostering career development, conducting hiring, and ensuring a high-performance, collaborative environment; • Define the strategic vision and roadmap for our AI agents platform, ensuring alignment with business needs and a focus on reuse, governance, and real impact; • Manage the AI project portfolio from conception to production, controlling schedules, prioritizing the backlog, and communicating progress to stakeholders; • Ensure the implementation of guardrails and best practices, guaranteeing the safety, quality, and reliability of AI solutions developed by the team; • Lead the structuring and evolution of GenAI Ops practices, including experimentation, versioning, evaluation, and continuous monitoring; • Act as the focal point between the data science team and engineering and product teams, translating business needs into scalable technical solutions; • Promote a culture of innovation, encouraging the team to experiment with techniques such as RAG, embeddings, and prompting to continuously improve performance.

• Develop advanced AI solutions: Design and implement intelligent agents (e.g., ReAct), integrating tools, APIs, and data to automate processes and deliver business value; • Work with end-to-end autonomy: Provide technical leadership across the delivery lifecycle, from experimentation (RAG, embeddings, advanced prompting, fine-tuning) to productionalization of models; • Write excellent code: Develop in Python with a focus on scalability, maintainability, and software engineering best practices, ensuring production-ready quality; • Support the setup of LLMOps/GenAI Ops: Implement robust evaluation (evals) pipelines, versioning, and continuous monitoring for generative AI solutions; • Act as a day-to-day mentor: Support the technical development of mid-level and junior data scientists through knowledge sharing, code reviews, and pair programming; • Collaborate with multidisciplinary teams: Work alongside data engineers, machine learning engineers, and architects to ensure models run efficiently on Databricks.

• Champion cutting-edge machine learning and AI techniques to improve holistic client engagement, personalization, and overall growth. • Represent our core algorithmic capabilities in cross-functional forums, including with our executive leadership team, synthesizing business requirements and translating technical solutions with radical transparency and a solution-oriented mindset. • Lead and inspire a team building transformative capabilities at the heart of our company’s value proposition, synthesizing and balancing multiple business objectives. • Foster a culture of ownership for holistic business outcomes within the team, encouraging proactive engagement with cross-functional partners. • Drive the development and optimization of our prediction and recommendation algorithms, ensuring they provide personalized, relevant, and engaging fashion recommendations for stylists and clients. • Oversee the end-to-end algorithm development lifecycle—from ideation and experimentation to testing and deployment in a production environment. • Manage the prioritization and execution of key algorithmic projects while balancing business needs, technical feasibility, and timelines. • Implement industry best practices for team collaboration, code quality, use of AI, and data management. • Stay up-to-date with the latest trends and advancements in AI-assisted development, AI-enabled product experiences, machine learning, and fashion technology.

• lead a workstream within Caremark's sales and underwriting analytics portfolio — owning end-to-end delivery as a senior individual contributor, setting technical direction, and mentoring peers • own multiple concurrent projects across model development, strategic analysis, and analytics product delivery — framing the business question, designing the approach, building the solution, and presenting findings to senior stakeholders • set technical direction for your workstream, mentor junior data scientists, and partner directly with business leaders across sales, underwriting, and finance to turn analysis into action