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Strong employer brand, mid-level generalist Data Scientist role with broad skills increases competition.
Core ML and forecasting skills transfer across industries, but healthcare workforce analytics adds moderate domain specificity.
Explicit 3+ years plus specific ML, statistical, and tooling requirements create moderate filtering.
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Develop and deploy predictive models for forecasting, demand planning, attrition prediction, capacity planning, and operational optimization.
Build automated analytics solutions and dashboards using Python, SQL, and Power BI to support strategic business decisions and improve operational efficiency.
Collaborate with business stakeholders and leadership to translate analytical insights into measurable business outcomes and drive AI-driven automation initiatives.
Post-Graduate degree in Statistics, Mathematics, or related quantitative discipline.
3+ years of experience in analytics, forecasting, data science, workforce analytics, or operations research.
Proficiency with machine learning algorithms including Random Forest, Decision Trees, Gradient Boosting, Regression, Classification, and Clustering.
Experience in SQL for data extraction and transformation, Power BI for data visualization, and demonstrated communication skills to explain complex analytics to non-technical stakeholders.
Proven track record of delivering measurable business impact via predictive analytics and automation in workforce or operations contexts.
Experienced in integrating machine learning models into business processes and collaborating cross-functionally with business leaders and operations teams.
Familiarity with advanced tools and frameworks like Scikit-Learn, Pandas, XGBoost, cloud analytics services (Azure/AWS/GCP), and MLOps for model deployment.