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.

+ 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.

_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._

** 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., Tensor Flow, 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…