Data Scientist

What you can expect

As our HR Data Scientist, you’ll work at the intersection of data science and HR, building predictive models and self-service analytics solutions on Databricks. You’ll partner with HR leaders, data engineers, and governance teams to turn workforce data into actionable insights while ensuring the highest standards of privacy, fairness, and security.

What you'll do

• Build predictive models to support hiring, retention, workforce planning, and employee performance;
• Partner with HR stakeholders to solve business challenges using data science and machine learning;
• Develop scalable ML pipelines using Databricks, MLflow, and Delta Lake;
• Create intuitive dashboards, Databricks Apps, and Genie rooms that empower HR teams with self-service insights;
• Translate complex analytics into clear, actionable recommendations for business leaders;
• Ensure models are accurate, ethical, and compliant with data privacy and governance standards;
• Monitor and continuously improve model performance as business needs evolve.

What you'll need

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, HR Analytics, or a related field;
• 3–5+ years of experience in Data Science or Machine Learning, ideally with HR or people analytics;
• Strong Python and SQL skills, with experience using machine learning libraries such as scikit-learn;
• Hands-on experience with Databricks or a similar cloud-based data science platform;
• Solid understanding of statistics, predictive modeling, and machine learning techniques;
• Experience working with sensitive data and applying privacy and ethical AI principles;
• Strong communication and stakeholder management skills, with the ability to explain technical concepts to non-technical audiences;
• Professional fluency in English, with strong written and verbal communication skills
• Nice to have: Experience with HR systems such as Workday, SAP SuccessFactors, or BambooHR; Experience with Databricks Genie, Dashboards, and Apps; Knowledge of Power BI, GDPR, explainable AI, and bias mitigation techniques; Experience using AI-assisted development tools and building self-service analytics solutions.