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, mobility, hiring, workforce planning). Hands‑on experience applying machine learning and statistical techniques to people‑related business problems, including supervised learning, feature engineering, and model evaluation. Demonstrated ability to translate HR business questions into analytical and predictive solutions, working closely with HR stakeholders. Experience working with complex, imperfect HR data and exercising sound analytical judgment around assumptions, limitations, bias, and uncertainty. Proficiency in Python or R, with the ability to communicate insights and recommendations clearly to non‑technical HR and business audiences. Working knowledge of data privacy, ethics, and responsible use of employee data. Experience applying tree‑based machine learning models such as Random Forest and XGBoost to people‑related analytics use cases (e.g., attrition risk, mobility, hiring outcomes). Experience or familiarity with unsupervised learning techniques (e.g., clustering, segmentation, anomaly detection) to explore workforce patterns and inform hypothesis generation. Familiarity with model explainability and governance in an HR context (e.g., feature importance, bias/fairness considerations, documentation, and model monitoring). Experience working with Workday data or HR systems (e.g., Workday reporting or Prism Analytics) is a plus. Working knowledge of SQL for data exploration and validation is a plus. Experience collaborating with data engineering to productionize models and analytics is a plus. Copilot and other AI experience. Minimum Qualifications Bachelors Degree plus 5 years' experience or Masters Degree plus 3 years' experience or PhD plus 0 years' experience. Base Pay Range $87,400.00 - $148,600.00 annually Primary Location USA-MI-Ann Arbor-KLA Benefits KLA’s total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program, development and career growth opportunities and programs, financial planning benefits, wellness benefits including an employee assistance program (EAP), paid time off and paid company holidays, and family care and bonding leave. Interns are eligible for some of the benefits listed. Equal Opportunity Employer KLA is proud to be an Equal Opportunity Employer. We will ensure that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us at View email address on click.appcast.io or at View phone number on click.appcast.io to request accommodation. #J-18808-Ljbffr