Build predictive models to forecast trends such as employee turnover, workforce engagement, and talent needs.
Develop prescriptive analytics solutions to inform HR strategies and optimize decision-making processes.
Analyze large datasets from various systems (e.g., Workday, Greenhouse) to uncover actionable insights.
Implement machine learning frameworks for solving HR-related challenges.
Harness insights from unstructured or qualitative data sources, such as performance reviews, annual engagement survey comments, or open-text survey responses.
Develop natural language processing (NLP) models to analyze text data and uncover trends, sentiment, or organizational themes.
Collaborate with stakeholders to define business problems, translate them into technical solutions, and communicate results effectively.
Integrate predictive outputs into Snowflake or visualization platforms like Tableau and Looker.
Partner with HR and data engineering teams to ensure seamless data pipeline management and integrity.
Maintain a strong focus on data accuracy, security, and compliance.

Requirements

5+ years of experience in data science roles, preferably in HR or People Analytics.
Ability to write complex, efficient, and eloquent SQL queries to extract data
Proficiency in programming languages such as Python or R for machine learning and statistical analysis.
Experience building and deploying machine learning models (e.g., decision trees, regression, clustering).
Strong statistical and problem-solving skills, with an emphasis on feature engineering and modeling.
Familiarity with Snowflake or equivalent data warehousing platforms for model integration.
Excellent communication skills to convey technical findings to non-technical audiences

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

predictive modelingprescriptive analyticsmachine learningnatural language processingSQLPythonRstatistical analysisfeature engineeringmodel deployment

Soft Skills

problem-solvingcommunicationcollaborationdata accuracy focusstakeholder engagement