Senior Manager, Statistical Modeling

About the role

Join Sallie Mae, a company dedicated to empowering students by providing them with the tools to navigate their educational journey confidently. We are committed to transforming how we serve students and are seeking a Senior Manager, Statistical Modeling to lead our efforts in developing and implementing advanced statistical models and methodologies.

Responsibilities

• Design, develop, and implement statistical and machine learning models and algorithms, aligning with organizational goals and digital transformation initiatives.
• Foster a collaborative and innovative work environment that encourages knowledge sharing, professional growth, and continuous improvement.
• Oversee the full model development and machine learning lifecycle: data collection, preprocessing, feature engineering, model development, deployment, and monitoring.
• Collaborate with cross-functional teams to translate business needs into effective modeling solutions.
• Ensure models are robust, reliable, and compliant with security, privacy, and governance standards.
• Develop and implement evaluation and validation procedures to ensure the accuracy, reliability, and scalability of statistical models.
• Generate regular reports and presentations to communicate results, insights, and recommendations to senior leadership and relevant stakeholders.
• Communicate results, insights, and recommendations to stakeholders through reports and presentations.
• Stay current with advancements in machine learning and data science, and evaluate new tools and technologies for adoption.

Requirements

• Master's degree in Statistics, Mathematics, Data Science, Computer Science, Data Science, Machine Learning, or a related field.
• 5+ years of experience in statistical modeling, including hands-on experience developing and deploying models in production environments.
• Proficiency in statistical programming languages such as Python, R, or SAS, and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of statistical modeling techniques, such as regression analysis, time series analysis, predictive modeling, and machine learning algorithms (supervised, unsupervised, deep learning, reinforcement learning).
• Experience with cloud-based platforms (e.g., AWS, Azure, Google Cloud).
• Familiarity with data engineering, data visualization, and model evaluation techniques.
• Excellent analytical and problem-solving abilities, with keen attention to detail.
• Effective communication and interpersonal skills, with the ability to present technical concepts to non-technical audiences.

Preferred

• Doctorate’s degree in Statistics, Mathematics, Data Science, Computer Science, Machine Learning, or a related field.
• 8+ years of experience in statistical modeling, machine learning, or data science, including managing large-scale ML projects.
• Experience with MLOps, containerization (Docker, Kubernetes), and deploying models in enterprise environments.
• Experience with data governance, security, and compliance in ML projects.