Data Scientist
17 hours ago
Role & responsibilities
DATA SCIENTIST - Higher Education Predictive Analytics
Preferred candidate profile
DATA SCIENTIST - Higher Education Predictive Analytics
Position Title: Data Scientist - Lead Scoring & Retention Modeling
Position Summary: The Data Scientist will develop and deploy machine learning models for Client institutions, focusing on lead scoring, student retention prediction, and enrollment forecasting. Working within Clients semi-Agile environment, the contractor will leverage GCP Vertex AI and BigQuery to deliver production-ready predictive solutions that drive student acquisition and success.
Core Responsibilities:
- Design and implement ensemble ML models (XGBoost, Random Forest, neural networks) for lead scoring using Vertex AI Custom Jobs
- Develop churn prediction models using survival analysis and cohort-based approaches in BigQuery ML
- Perform feature engineering with SQL on BigQuery datasets (demographic, behavioral, academic data)
- Deploy real-time scoring endpoints via Vertex AI and integrate with institutional CRM systems
- Create explainable AI dashboards for non-technical stakeholders (Deans, enrollment managers)
- Conduct A/B testing frameworks for pricing optimization and intervention strategies
- Track sprint progress and log hours in Azure DevOps 7Pace for transparent billing
- Ensure FERPA compliance in all model development and data handling processes
Required Technical Skills:
- GCP Vertex AI: Model training, AutoML, endpoint deployment, monitoring
- BigQuery: Advanced SQL, ML integration, scheduled queries, cohort analysis
- Python: scikit-learn, TensorFlow, pandas, numpy, SHAP/LIME for explainability
- Statistics: Logistic regression, time-series analysis, survival modeling, propensity scoring
- Azure DevOps 7Pace: Time tracking and sprint management
Higher Education Domain Expertise:
- Experience with student lifecycle analytics (inquiry enrollment retention graduation)
- Familiarity with enrollment funnel optimization and conversion rate modeling
- Knowledge of FERPA, data privacy in educational contexts
- Understanding of academic program pricing dynamics and elasticity modeling
Qualifications:
- Master's/PhD in Data Science, Statistics, or related field
- 5+ years ML experience; 2+ years GCP/Vertex AI
- Google Cloud Professional Data Engineer or ML Engineer certification preferred
- Proven track record delivering education analytics solutions
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