We are a hybrid, remote-office company dedicated to growing our talent anywhere!

We have onsite locations in: Sioux Falls, SD, Phoenix, AZ, Louisville, KY, Troy, MI, Franklin, TN, Easton, PA.

At Pathward, we take tremendous pride in our purpose to create financial inclusion for all™. We are a financial empowerment company that works with innovators to increase financial availability, choice, and opportunity for all. We strive to remove barriers that traditional institutions put in the way of financial access, and promote economic mobility by providing responsible, secure, high quality financial products.

We are a team of problem solvers and innovators who celebrate our differences and know that our unique perspectives make us stronger and well-positioned for success. We celebrate, and embrace, our team members through our *HUMBLE*HUNGRY*SMART approach, and we believe that we are strongest when we embrace the voices of our employees, customers, partners, and the communities we serve.

About the Role

The Data Scientist I supports analytical solutions, model and partner oversight, data quality, and decision-making across the organization. This role combines hands-on data analysis with partner onboarding and monitoring, business-focused data quality investigation, model monitoring, and technical documentation.

The successful candidate will work with Data Science, business, risk, technology, and external partners to analyze data, identify issues and opportunities, monitor performance, and document analytical solutions. The role will also leverage approved AI and productivity tools to improve the efficiency and quality of analysis, coding, and documentation.

What You Will Do

Analyze large and complex datasets using statistical, predictive, and other analytical techniques to generate actionable business insights.
Support development, testing, implementation, and monitoring of predictive models and analytical solutions.
Support partner model and program onboarding, oversight, and ongoing monitoring, including data validation, performance analysis, documentation, and issue resolution.
Perform data quality analysis with business context, identifying root causes, downstream impacts, and opportunities to improve data reliability and usability.
Develop and maintain monitoring processes for models, partner portfolios, products, and critical data.
Create comprehensive technical documentation covering data, methodologies, business requirements, testing, model performance, monitoring, assumptions, and limitations.
Use approved AI-assisted tools to improve documentation, coding, analysis, quality assurance, and workflow efficiency while independently validating outputs.
Collaborate with business, risk, compliance, technology, operations, vendors, and external partners to implement and maintain analytical solutions.
Develop reusable and automated processes to improve monitoring, reporting, data validation, and Data Science workflows.
Communicate analytical findings, risks, and recommendations clearly to technical and nontechnical stakeholders.

What You Will Need

Bachelor’s degree in Data Science, Statistics, Mathematics, Economics, Engineering, Computer Science, Finance, Business Analytics, or a related quantitative field.
Up to 2+ years of relevant professional, internship, research, or project experience.
Experience working with large datasets and applying analytical or statistical methods to business problems.
Hands-on experience with Python and SQL for data analysis, validation, and automation.
Strong analytical and problem-solving skills with the ability to connect technical findings to business processes and outcomes.
Experience with data profiling, reconciliation, root-cause analysis, and data quality validation.
Strong written communication skills with the ability to produce detailed technical and analytical documentation.
Ability to manage multiple analytical, monitoring, and documentation responsibilities with strong attention to detail.
Curiosity and willingness to learn new business areas, analytical techniques, technologies, and AI-enabled tools.