We have an exciting opportunity to join our team as a Predictive Analytics Analyst. In this role, the successful candidate is responsible for leveraging advanced statistical and machine learning techniques to generate actionable insights from HR and business data. This role designs and develops predictive models (e.g., for performance, turnover, and hiring outcomes), automates data integration between spreadsheets and HR systems, and builds robust data pipelines to ensure timely, accurate reporting. Partnering closely with HR and cross-functional teams, the analyst translates complex analyses into clear, practical recommendations that support workforce planning, talent strategies, and organizational performance. The position requires strong technical skills in Python/ R and relational databases, a solid grounding in statistics and data science, and the ability to communicate insights effectively to non-technical stakeholders while driving continuous improvement in People Analytics methodologies and practices. Job Responsibilities:Lead or contribute to cross-functional People Analytics projects, overseeing data pipelines, predictive modeling, and stakeholder engagement. Perform advanced statistical analyses (e.g., tests, non-parametric tests, multivariate analysis, winsorization) to evaluate salary band positioning, tenure, performance trends, turnover analysis, and pay equity. Augment analytical report outputs with fact-based examples, observations, and recommendations that guide informed decision-making. Keep up to date with new academic and industry developments in data analytics, machine learning, data science, people analytics, and HR technology, and incorporate relevant methods into practice to continuously improve analytical methods and predictive modeling approaches. Provide data insights and suggestions to solve complex HR and business problems by formulating, developing, and interpreting statistical and machine learning models. Derive actionable insights from structured and unstructured HR data (e.g., HRIS, ATS, performance, engagement, compensation, etc.). Communicate analytical results clearly and succinctly through presentations, dashboards, and written narratives tailored to non-technical stakeholders. Work closely with HR and business leaders to make value-added analytical services available to internal customers. Be creative, collaborative and a self-starter, proactively identifying opportunities to use analytics to improve HR and business outcomes. Minimum Qualifications:To qualify you must have a Bachelor's Degree is required. Strong preference in Statistics, Mathematics, Computer Science, Data Science, Economics, industrial/systems engineering, information management, epidemiology, or other related quantitative skills. 3 or more years of experience in predictive modeling and data mining using large and complex datasets; experience in People Analytics / HR analytics strongly preferred (experience in other analytics-heavy domains such as insurance, financial services, or retail is also valuable). Hands-on experience with Python, R, SQL, cloud platforms, and machine learning. Hands-on experience building predictive models (e.g., linear and logistic regression, GLM, decision trees, cluster analysis, principal components, feature creation and validation) using Python and/or R. Experience leading or contributing to cross-functional analytics projects, coordinating data pipelines, modeling workstreams, and stakeholder communication. Data visualization and dashboarding (e.g., Power BI, Tableau, or similar). Strong written and verbal communication skills for explaining complex analyses to non-technical stakeholders. Qualified candidates must be able to effectively communicate with all levels of the organization.