Principal Data Scientist

Lumentum•Greensboro, NC

8d•$149,900 - $214,150

About The Position

As a Principal Data Scientist at Lumentum Operations LLC, you will lead the development and deployment of advanced analytical solutions to drive business innovation and operational excellence. You will leverage your expertise in data science, machine learning, and statistical modeling to extract actionable insights from complex datasets and inform strategic decisions across various functions.

Requirements

Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
15+ years of progressive experience in data science, applied statistics, manufacturing analytics, process engineering, yield engineering, operations research, or a closely related discipline.
Advanced degree in statistics, data science, industrial engineering, electrical engineering, materials science, physics, operations research, or a related quantitative field; equivalent experience may be considered.
Demonstrated experience applying advanced analytics and statistical modeling in photonics, semiconductor, optical-component, wafer, electronics, or similarly complex manufacturing environments.
Deep understanding of FAB and factory processes, including process control, yield analysis, equipment behavior, production flow, test, quality, and manufacturing execution systems.
Expert knowledge of experimental design, DOE, regression, multivariate analysis, time-series modeling, anomaly detection, causal analysis, and statistical process control.
Advanced programming skills in Python and SQL; strong experience working with large, complex, and high-dimensional datasets.
Experience developing analytical solutions that are adopted by engineering, manufacturing, quality, or operations teams.
Demonstrated ability to influence senior technical and business stakeholders across organizational boundaries.
Strong executive communication skills, including the ability to explain complex statistical and technical findings in clear business language.
Proven record of technical leadership, mentoring, and raising analytical standards without requiring direct people-management authority.

Responsibilities

Lead the data-science and advanced-analytics agenda for FAB and factory operations.
Partner with manufacturing and engineering leaders to frame problems, define analytical requirements, and prioritize analytical work.
Analyze FAB and factory processes, including yield, process variability, excursions, equipment behavior, throughput, bottlenecks, cycle time, WIP, rework, test fallout, quality, and scrap.
Develop and apply statistical, predictive, and prescriptive models using complex, high-volume manufacturing data.
Design and evaluate experiments, including DOE and controlled analyses, to understand process drivers and validate improvement actions.
Apply regression, multivariate analysis, time-series methods, anomaly detection, causal reasoning, SPC, and other advanced statistical techniques.
Establish trusted analytical definitions, features, and data structures across lots, products, process steps, equipment, recipes, materials, test results, defects, and production events.
Work with data engineering and platform teams to productionize datasets, features, models, and analytical applications.
Support analytics across MES, SPC, FDC, R2R, equipment, test, quality, ERP, supply-chain, and planning systems.
Review analytical methods and results for statistical rigor, data quality, interpretability, and practical usability.
Communicate technical findings, assumptions, uncertainty, tradeoffs, and recommendations to engineers, operators, business leaders, and executives.
Build reusable analytical methods, documentation, validation standards, and model-monitoring practices.
Mentor data scientists, analysts, and engineers in statistical thinking, problem framing, modeling, and technical communication.
Represent Corporate Analytics & Data Science as a trusted technical advisor to manufacturing and operations leadership.