HR Analytics Data Scientist

KLA • Milpitas, CA

2d

About The Position

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.

Requirements

• 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.
• Bachelors Degree plus 5 years' experience or Masters Degree plus 3 years' experience or PhD plus 0 years' experience

Nice To Haves

• 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

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

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees