• Lead studies including (but not limited to) a combination of healthy volunteer and patient populations, multi-site, complex protocol design, strong client management required or reduced timelines. • Ability to organize and effectively prioritize workload and deliverables. • As the Study Manager, be accountable for all DM deliverables as assigned per the established timeline; providing instruction to their DM study team(s) and review of their study team’s output to ensure the highest quality, while adjusting resource allocations accordingly. • Ensure that all allocated projects are carried out in strict accordance with the relevant protocols, global harmonized SOPs, and the specified standards of GCPs. • Work with the Project Manager(s) or FSP Lead (or designee) to build timelines to meet contracted milestones by communicating with leads in different disciplines and the full project team as necessary, including at study initiation meetings. • Provide DM project team leadership and accountability; leads data focused internal project team meetings; meets frequently with the study leads of EDC Design, SAS Programming, Statistics, and PK to ensure that all deliverables are planned and coordinated intradepartmental; proactively identifies potential risks/mitigations, effectively communicates data-driven discussions in order to achieve database lock dates; keeps the Project Manager or FSP Lead (or designee) apprised of project progress. • Maintain awareness of other Biometrics functional group deliverables to be able to support risk and mitigation strategies, including impact on DM resources or deliverables and consult with Project Manager (or designee) and/or functional group management as necessary.

• Develop machine learning models to support decision-making in the installment lending business • Build AI features and LLM-based applications • Work closely with Data Engineering, Product Management, and Data Analytics • Take end-to-end responsibility for machine learning models • Continuously advance data-driven products and use cases

Role Description Be part of a team that values safety, inclusion, and excellence. As a member of our team, you will play a role in supporting the movement of essential products and materials that help feed, clothe, supply, and power communities throughout America and the world. Are you ready to drive change? If you are passionate about making a difference and eager to advance your career in a dynamic and supportive environment, we want you on our team! Join us in reshaping the future of freight rail and discover a fulfilling career where your contributions matter. This position is open to candidates who are currently authorized to work in the United States. We are also open to sponsoring H-1B transfers, TN nonimmigrant status, and STEM OPT candidates with at least 2 years of remaining eligibility. Qualifications - Minimum of 2 years experience building data science solutions or relevant experience. - Demonstrated understanding of statistical analysis and machine learning techniques. - Experience with data visualization tools. - Proficiency in programming languages such as Python, R, SQL, and familiarity with Java or Scala. - Experience with data science cloud platforms. Requirements - Work with cross-functional teams to identify business problems and develop data-driven solutions. - Apply data science skills to analyze large, complex datasets and identify meaningful patterns that lead to actionable insights. - Develop and implement machine learning models to predict outcomes and improve processes. - Collaborate with stakeholders to understand their needs and provide actionable insights. - Create visualizations and reports to communicate findings effectively. - Maintain and update data pipelines to ensure data integrity and accuracy. - Stay current with industry trends and advancements in data science and machine learning. - Identify, extract, aggregate, and synthesize data using SQL and NoSQL databases, R, Python or other appropriate languages. - Drive moderate to complex data science, machine learning, traditional artificial intelligence, generative artificial intelligence or optimization projects. - Demonstrate operational excellence by monitoring, troubleshooting, and resolving production issues. Benefits - An industry-leading 401(k) and renowned Railroad Retirement program. - A range of robust health care options for you and your dependents, including medical, dental, vision, telemedicine, mental health, and cancer support. - Health care spending accounts (HSA) with employer contributions, as well as life and disability insurance, provided at no cost. - Family benefits including parental, pediatric and family building support, adoption and surrogacy reimbursement, and dependent care spending account (with employer match). - Access to discounts on travel, gym memberships, counseling services and wellness support. - Annual bonus (Incentive Compensation Program). - Generous leave / time off policies.

• Lead the development and implementation of a comprehensive biomedical research data governance program across SMPH, including best practices for research data stewardship and lifecycle management. • Partner with investigators to develop and implement data management and sharing plans for grant applications, ensuring alignment with funding agency requirements and FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. • Facilitate the discoverability, documentation, and dissemination of research datasets, including support for assigning persistent identifiers (e.g., DOIs), developing metadata standards, and depositing datasets into institutional and national repositories. • Establish and oversee data quality, data curation, and data stewardship frameworks that promote the accuracy, consistency, completeness, and usability of research data assets. • Lead the design and implementation of data integration, linkage and secure release methodologies spanning structured, semi-structured, textual, imaging, and other heterogeneous biomedical data sources. • Develop processes, standards, and tools that improve interoperability and enable the secure integration of research, clinical, public health, and other data domains to support advanced research initiatives while protecting privacy of patients and participants in research studies. • Guide the development and use of de-identified, limited, and synthetic datasets that support research access while maintaining appropriate safeguards for PHI and compliance with institutional policies. • Develop and implement methodologies for creating research-ready data products that enable reproducible, secure, scalable, and efficient research workflows. • Conduct and oversee data quality assessments, validation activities, and data fitness-for-use evaluations to ensure that research datasets meet established governance and scientific standards. • Serve as a subject matter expert in biomedical data governance, advising investigators, departmental leaders, and research teams on data stewardship, data sharing, metadata standards, and responsible data use. • Develop and deliver training, educational resources, and consultation services that promote best practices in research data management and governance across SMPH. • Monitor emerging trends, technologies, and policies related to biomedical data governance, FAIR data practices, research data ecosystems, interoperability standards, and advanced data management methodologies. • Directly and indirectly supervise staff supporting research data operations, data stewardship programs, data curation activities, and institutional data governance initiatives across SMPH.