HR Analytics Data Scientist

Company Overview

KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us.

Group/Division

The vision of KLA’s global human resources organization is to become a leader and partner to operating leadership in support of the company’s efforts to achieve its strategic growth, customer and operating objectives through strategic talent management. Our mission is to enable the business, and leverage human resources to achieve short and long-term business objectives. Our primary areas of strategic focus include talent acquisition, individual and organizational assessment and development, performance management, inclusion and engagement, and rewards. The global HR organization includes HR business partners, learning and development, talent acquisition, compensation and benefits, employee communications, and HR system operations.

Job Description/Preferred Qualifications

The HR Data Scientist will play a key role in advancing KLA’s HR Analytics capability by building scalable AI and predictive insights on top of established workforce data, reporting, and core metrics.  The Data Scientist will partner closely with the Analytics team, HR Business Partners, Centers of Excellence, and HR leadership, to translate workforce and talent questions into high‑impact analytical and predictive solutions. The position focuses on applying AI techniques and predictive analytics to better anticipate workforce risks and opportunities, building and maintaining robust models, and uncovering drivers of key workforce outcomes to deliver clear actionable insights to support more proactive data‑driven decision‑making.

Key Responsibilities

• Partner with HRBPs, COEs, and HR leadership to frame business questions, define hypotheses, and translate needs into analytics solutions across descriptive, predictive, and prescriptive use cases.

• Analyze workforce data using statistical and analytical methods to identify key patterns, drivers, and relationships (e.g., engagement, attrition, mobility, hiring outcomes).

• Design, build, validate, and maintain predictive models (e.g., attrition risk, internal mobility, workforce demand, workforce planning, TA funnel outcomes), including feature engineering, evaluation, and ongoing monitoring.

• Design and build AI analytic tools to help with the acceleration of data insights

• Own end‑to‑end analytics delivery for more advanced analytics use cases from data exploration and modelling through insight generation, storytelling, and clear recommendations for decision‑makers.

• Develop reusable analytical assets (model templates, code libraries, documented methodologies, metric definitions) to enable scalable and repeatable analytics across HR.

• Ensure data integrity and reliability by auditing datasets, diagnosing issues, and implementing data quality checks and controls.

• Collaborate closely with HR Data Engineering and IT to improve datasets, pipelines, and the overall analytics foundation (Workday/Prism and other Analytics platforms and external sources).

• Establish and follow data privacy, ethics, and governance practices for employee data, including appropriate use, fairness and bias considerations, transparency, and access control.

• Contribute to the HR analytics roadmap by identifying high‑value predictive use cases and opportunities to automate insight delivery

Preferred Qualifications:

• Bachelor’s degree in a quantitative or analytical field (e.g., Statistics, Math, Economics, Engineering, Data Science) or equivalent practical experience.

• 2+ years of experience in data science or advanced analytics roles, with direct experience working on HR / people / workforce analytics (e.g., attrition, engagement,