Sr Principal Data Scientist, Search and Recommendations

About the role

We are seeking an experienced Data Scientist / Senior Consultant to drive the science and strategy behind Ingram Micro’s global Search and Recommendation systems.

Responsibilities

• Own multi-quarter technical development, vision, and roadmap for search, ranking, personalization, discovery, and recommendation systems.
• Engage with a globally distributed team of Data Scientists and AI/ML Engineers.
• Be accountable for model quality, experimentation rigor, and production impact.
• Influence platform, tooling, and architecture decisions in partnership with science, engineering, and business leadership.

Qualifications

• Master’s or Ph.D. in a quantitative field (Computer Science, Data Science, AI, Statistics, Applied Math, Engineering, Economics, or similar technical fields)
• 10+ years functional experience including a minimum of 5+ years position specific experience in search, recommendation, information retrieval, or personalization at scale
• Track record of owning production search or recommendation systems with measurable business impact
• Hands-On Technical Ownership
• Expertise in developing and leading the deployment of enterprise level Search Algorithms and Recommendation Engines at global scale
• Develop model design for ranking, relevance, personalization, semantic retrieval
• Build applications leveraging LLMs, deep learning, transformers, generative AI, semantic search, vector databases, and RAG pipelines
• Design and interpret A/B tests and quasi-experiments tied to business metrics
• Tools/stack experience: Python, SQL, Jupyter, R, Julia, SAS, MATLAB, etc...
• Experience with GCP (Big Query, VertexA, Gemini) strongly preferred
• Experience developing Search/Recommendation Agents is a plus
• Work with large-scale behavioral, content, and transactional datasets to solve highly ambiguous problems

Organizational & Technical Leadership

• Partner with and mentor mid- and senior-level scientists
• Set bar for modeling excellence, experimentation discipline, production readiness
• Promote reusable ML platforms and standardization over one-off solutions
• Serve as an executive-facing authority on search and recommendation science

Stakeholder & Business Leadership

• Translate ambiguous business problems into scalable AI and ML solutions
• Communicate technical models, engines, systems to non-technical stakeholders
• Partner with Product, Engineering, and Business to balance near-term wins vs. long-term platform bets