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.

The Manager, Statistical Modeling will be responsible for leading a team of statistical analysts and driving the development and implementation of statistical models and methodologies.

• Contribute to the development and execution of the statistical modeling strategy, aligning it with the organization's goals and objectives.
• Foster a collaborative and innovative work environment that encourages knowledge sharing, professional growth, and continuous improvement.
• Design and develop statistical models, algorithms, and methodologies to analyze complex data sets and solve business problems.
• Analyze and interpret large and diverse data sets to identify patterns, trends, and correlations.
• 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.

The above information is intended to describe the general nature and level of work performed by employees assigned to this job; it is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees in this role.

• Master's degree in Statistics, Mathematics, Data Science, Computer Science, Machine Learning, or a related quantitative field.
• 3+ years of experience in statistical modeling, including experience with developing and implementing statistical models.
• Proficiency in statistical programming languages such as R, Python, or SAS.
• Knowledge of statistical modeling techniques, such as regression analysis, time series analysis, predictive modeling, and machine learning algorithms.
• Familiarity with data visualization tools and techniques to effectively communicate data insights.
• Excellent analytical and problem-solving abilities, with a keen attention to detail.
• Effective communication and interpersonal skills, with the ability to collaborate with stakeholders at various levels of the organization.

• Doctorate’s degree in Statistics, Mathematics, Data Science, Computer Science, Machine Learning, or a related quantitative field.
• 5+ years of experience in statistical modeling, including experience with developing and implementing statistical models.
• 3+ years of experience in machine learning, including hands-on experience developing and deploying ML models in production environments.
• Proficiency in statistical programming languages such as Python, R, or Java, and familiarity with ML frameworks (e.g., Tensor Flow, PyTorch, Scikit-learn).
• Stron…