Sr Principal Data Scientist, Search and Recommendations

Ingram Micro • Irvine, CA

1d

About The Position

Accelerate your career. Join the organization that's driving the world's technology and shape the future. Ingram Micro is a leading technology company for the global information technology ecosystem. With the ability to reach nearly 90% of the global population, we play a vital role in the worldwide IT sales channel, bringing products and services from technology manufacturers and cloud providers to business-to-business technology experts. Our market reach, diverse solutions and services portfolio, and digital platform Ingram Micro Xvantage™ set us apart. Learn more at www.ingrammicro.com Come join our team where you’ll make technology happen in surprising ways. Let’s shape tomorrow - it’ll be a fun journey! We are seeking an experienced Data Scientist / Senior Consultant to drive the science and strategy behind Ingram Micro’s global Search and Recommendation systems. The role partners closely with a diverse team of scientists, engineers, product leaders, and industry experts to build large‑scale models that meaningfully improve discovery, relevance, and commercial outcomes across an enterprise ecosystem. You will be responsible for the technical strategy, model development, experimentation, and production impact, delivering measurable improvements to the performance of search and recommendation engines worldwide. The role is hands‑on and high‑visible requiring deep technical expertise and the ability to communicate complex concepts to non‑technical audiences.

Requirements

• 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
• 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…
• Work with large‑scale behavioral, content, and transactional datasets to solve highly ambiguous problems

Nice To Haves

• Experience with GCP (Big Query, VertexA, Gemini) strongly preferred
• Experience developing Search/Recommendation Agents is a plus

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
• 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
• 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

Benefits

• U.S.-based employees have access to healthcare benefits, paid time off, parental leave, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, and wellbeing benefits, among others.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level