Senior Manager, Statistical Modeling

Senior Manager, Statistical Modeling

When you join Sallie Mae, you become a champion for all students. We're on a mission to power confidence as students begin their unique journey. To help them plan their higher education, successfully finish, and prepare for life after school. To help them Start smart. Learn big. Students need guidance navigating this important time in their life. They need someone who acknowledges that their education path is unique. They need a partner willing to evolve and not only meet but surpass their expectations. We're changing. Because students need a better way. We're looking for people who are excited to drive this transformation. To break barriers and think of new ways to adapt, help, and create better experiences for students—and for each other. This is where diverse backgrounds, beliefs, and perspectives matter. It's where you're empowered to bring your authentic self to work. Feeling your best allows you to do your best. Our benefits take care of the whole you—from physical and mental to financial and professional. You'll get opportunities to further your education and career, support for you and your family (including your pets!), paid time off to volunteer for the things that matter to you, and more. We're obsessed with impact and making a real difference. For us, that means putting relationships first, asking "why not?" when tackling challenges, and continuously learning new skills. Come do more than join something, change something. For students, for future generations, for the future of education.

What You'll Contribute

The Senior Manager, Statistical Modeling will be responsible for developing and implementing advanced statistical models and methodologies to analyze complex data sets, extract insights, and provide actionable recommendations.

What You'll Do

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.

What You Have

Minimum: Indicate minimum education, skills and experience required. 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: Indicate "nice to haves" regarding education, skills, and experience. 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.