Sr Principal Data Scientist, Search and Recommendations (Irvine)
Sr Principal Data Scientist, Search and Recommendations page is loaded Sr Principal Data Scientist, Search and Recommendationslocations: Irvine, CA, United States of Americatime type: Full timeposted on: Posted Todayjob requisition id: R-113931 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 atCome 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. Scope * 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 Success Metrics * Sustained improvements in relevance, engagement, and conversion* High-retention, high-performing ML team with strong internal mobility* Systems that scale globally with reliability and defensible scientific rigor* Measurable impact to financial results and customer experienceLI-RT1 The typical base pay range for this role across the U.S. is USD $158,900.00 - $270,100.00 per year.The ranges above reflect the potential annual base pay across the U.S. for all roles; the applicable base pay range will depend on the candidate’s primary work location, pay grade, and variable compensation plan. Individual base pay within each range depends on various factors, in addition to primary work location, such as complexity and responsibility of role, job duties/requirements, and relevant experience and skills. Base pay ranges are reviewed and typically updated each year. Offers are made within the base pay range applicable at the time of hire. New hires starting base pay generally falls in the bottom half (between the minimum and midpoint) of a pay range.At Ingram Micro certain roles are eligible for additional rewards, including merit increases, annual bonus or sales incentives and long-term incentives. These awards are allocated based on position level and individual performance. 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.This is not a complete listing of the job duties. It’s a representation of the things you will be doing, and you may not perform all these duties.Please be prepared to pass a drug test and successfully pass a pre-employment (post offer) background check.Ingram Micro Inc. is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected category under applicable law. J-18808-Ljbffr
