Doctor of Philosophy in Faith-Based Data Science, Specialization in Analytics for Social Impact

Degree abbreviation

Ph.D. in Faith-Based Data Science

Total program length

120 semester credit hours

Normal completion time

Four to six academic years, depending on approved transfer credit, enrollment status, research progress, and dissertation completion

Academic unit

HBIU College of Computer Science

Total credits

120

Duration

3 years

• Analyze complex social datasets using advanced statistical models and machine learning algorithms.
• Evaluate the ethical implications of data-driven decision-making within the context of servant leadership and social justice.
• Design original, data-centric research that addresses systemic challenges faced by community-based organizations.
• Integrate biblical stewardship principles into the lifecycle of data management and algorithmic development.
• Communicate technical research findings to diverse stakeholders to advocate for data-informed policy and operational improvements.
• Demonstrate advanced competency in computational social science methods to support organizational mission-driven goals.
• Course Outline
• Semester 1 — Year 1
• Code
• Title
• Credits
• Prerequisites
• RES700
• Advanced Quantitative Methods
• 4
• None
• THE701
• Ethical Reasoning and Digital Stewardship
• 3
• None
• RES705
• Research Design and Social Impact
• 3
• None
• RES700 — Advanced Quantitative Methods: This course covers complex statistical analysis, multivariable modeling, and advanced computational techniques used in social research. Students develop the ability to handle high-dimensional datasets while ensuring methodological rigor. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• THE701 — Ethical Reasoning and Digital Stewardship: This course explores the intersection of data ethics, moral philosophy, and the biblical concept of stewardship in the digital age. It emphasizes the responsibility of data scientists in maintaining the dignity and privacy of those they serve. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• RES705 — Research Design and Social Impact: Students learn to formulate research questions that effectively address social problems through data science. The course focuses on bridging the gap between theoretical modeling and practical application in the field. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• Semester 2 — Year 1
• Code
• Title
• Credits
• Prerequisites
• DAT710
• Machine Learning for Social Good
• 4
• RES700
• SOC720
• Data Visualization and Community Narrative
• 3
• None
• MGT730
• Data Governance and Leadership
• 3
• None
• RES715
• Qualitative Inquiry in Data Science
• 3
• None
• DAT710 — Machine Learning for Social Good: This course provides advanced study in supervised and unsupervised learning techniques applied to social services and human behavioral data. Students evaluate the outcomes of models through the lens of justice and fairness. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• SOC720 — Data Visualization and Community Narrative: Focuses on the visual communication of complex datasets to empower community leaders and stakeholders. Students learn to translate raw data into narratives that support organizational advocacy and strategic planning. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• MGT730 — Data Governance and Leadership: Examines the structures necessary for responsible data management and organizational transparency in nonprofit environments. Leadership principles for the data-driven organization are discussed in the context of servant leadership. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• RES715 — Qualitative Inquiry in Data Science: Introduces mixed-methods approaches that combine quantitative data with qualitative insights to understand social phenomena. Students learn to interpret the lived experience of stakeholders alongside their data-driven behaviors. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• Semester 3 — Year 2
• Code
• Title
• Credits
• Prerequisites
• DAT740
• Predictive Analytics for Community Resources
• 4
• DAT710
• RES750
• Doctoral Research Seminar I
• 3
• RES705
• BUS760
• Economic Impact of Social Interventions
• 3
• None
• SOC770
• Algorithmic Bias and Social Equity
• 3
• None
• DAT740 — Predictive Analytics for Community Resources: Students learn to build predictive models to optimize the allocation of scarce social resources. The course emphasizes cost-benefit analysis and outcome measurement for mission-driven initiatives. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• RES750 — Doctoral Research Seminar I: This seminar facilitates the preliminary development of the dissertation research proposal. Students refine their methodology, define scope, and prepare for institutional ethical board review. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• BUS760 — Economic Impact of Social Interventions: Focuses on quantifying the financial and social impact of interventions on underserved populations. Students analyze data to demonstrate organizational efficiency and social return on investment. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• SOC770 — Algorithmic Bias and Social Equity: An investigation into systemic biases inherent in big data and automated decision-making systems. Students develop strategies to detect and mitigate bias in order to promote equity in service delivery. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• Semester 4 — Year 2
• Code
• Title
• Credits
• Prerequisites
• RES780
• Doctoral Research Seminar II
• 4
• RES750
• DAT790
• Data Privacy and Security for Nonprofits
• 3
• None
• MGT810
• Collaborative Leadership in the Data Age
• 3
• None
• SOC820
• Sociological Frameworks for Community Development
• 3
• None
• RES780 — Doctoral Research Seminar II: Students engage in literature review completion and initial data collection strategies for their specific dissertation topics. Regular critiques and feedback sessions are conducted within this peer-support framework. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• DAT790 — Data Privacy and Security for Nonprofits: This course reviews the security architecture and regulatory compliance requirements for handling sensitive community data. Students implement strategies to ensure the highest standards of data stewardship. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• MGT810 — Collaborative Leadership in the Data Age: Explores how leaders can bridge the gap between technical teams and organizational visionaries. Students study servant leadership models that foster cross-departmental cooperation and mission clarity. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• SOC820 — Sociological Frameworks for Community Development: This course explores historical and contemporary models of community development through the lens of social capital and institutional change. Students evaluate the effectiveness of various interventions in addressing systemic urban and rural challenges. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• Semester 5 — Year 3
• Code
• Title
• Credits
• Prerequisites
• RES830
• Advanced Dissertation Research I
• 4
• RES780
• DAT840
• Applied Network Analysis for Communities
• 3
• None
• BUS850
• Strategic Implementation of Data Strategies
• 3
• None
• SOC860
• Global Perspectives in Data for Good
• 3
• None
• RES830 — Advanced Dissertation Research I: Focuses on primary data analysis and the drafting of initial dissertation chapters under faculty mentorship. Students document their research progress and integrate findings into their broader dissertation framework. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• DAT840 — Applied Network Analysis for Communities: Explores the use of graph theory and network analysis to understand community structures and resource flows. Students apply these models to map social capital and outreach effectiveness. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• BUS850 — Strategic Implementation of Data Strategies: Covers the implementation phase of data-driven projects in a service-oriented setting. Focuses on change management, organizational adoption of new technologies, and continuous improvement. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• SOC860 — Global Perspectives in Data for Good: Evaluates global case studies where data has been effectively leveraged to address international challenges like hunger, housing, and disease. Students compare diverse institutional approaches to social impact. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• Semester 6 — Year 3
• Code
• Title
• Credits
• Prerequisites
• RES890
• Final Dissertation Defense
• 4
• RES830
• RES880
• Advanced Dissertation Research II
• 3
• RES830
• COM870
• Public Scholarship and Advocacy
• 3
• None
• MIN885
• Formation for Servant Leadership
• 3
• None
• RES890 — Final Dissertation Defense: In this final stage, candidates complete the writing of their dissertation, undergo a formal final review, and present their defense before the faculty committee. Completion of this course signifies the final requirement for the PhD. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• RES880 — Advanced Dissertation Research II: Candidates focus on finalizing the synthesis of their quantitative findings with their theoretical framework and ethical reflections. This stage ensures the research meets the highest scholarly standards of academic excellence. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• COM870 — Public Scholarship and Advocacy: Focuses on the translation of doctoral research for public discourse, policy advocacy, and community education. Candidates practice effectively communicating the results of their work to non-specialist decision-makers. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• MIN885 — Formation for Servant Leadership: Integrates the candidate's research experience with reflections on personal and professional formation as a leader of character. Students finalize their development plan for ongoing service in the field. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.

Admission to the Doctor of Philosophy in Faith-Based Data Science requires a completed master's degree from an accredited institution in a relevant field such as Computer Science, Data Analytics, Statistics, or a closely related discipline. Applicants must provide official academic transcripts, a statement of research intent, letters of recommendation, and evidence of proficiency in quantitative methodology. Prospective students are evaluated on their academic preparation, professional experience in community or social impact roles, and the alignment of their research interests with the university’s mission of ethical, faith-informed service. Dissertation Requirement The Dissertation represents the culminating intellectual achievement of the PhD program, requiring students to execute an original, independent research project that advances the field of data science within a social impact framework. Students are expected to identify a significant, real-world problem and apply rigorous quantitative methods to generate actionable insights or theoretical developments. The scope of this research must reflect a commitment to ethical rigor and practical utility for organizations dedicated to the public good. The dissertation process integrates the student’s academic technical expertise with faith-informed character development, emphasizing biblical stewardship, ethical integrity, and a commitment to serving others through scholarship. Students must defend their findings before a committee, demonstrating both the quality of their computational research and their ability to articulate how their work promotes a vision of justice and flourishing. Through this process, candidates demonstrate not only scholarly mastery but also the capacity for servant leadership and the capacity to synthesize technical truth with the moral foundations of their faith.

• Graduation requirements include the successful completion of 120 credit hours with a minimum cumulative GPA of 3.0 on a 4.0 scale. Students must demonstrate proficiency in all required doctoral coursework and receive final approval from their dissertation committee upon the successful defense of their doctoral research. All course requirements must be completed within the designated academic timeframe to ensure the currency of the student’s training.
• Beyond academic milestones, the university expects graduates to reflect the character of a faith-informed leader. This includes demonstrated engagement in spiritual formation, active participation in the academic community, and adherence to the university’s code of ethical conduct. Students are prepared for service by demonstrating a commitment to academic excellence paired with the moral humility and integrity required to steward data resources for the advancement of their community and the realization of their organization’s mission.
• Career Opportunities
• Chief Data Officer in non-profit and faith-based organizations
• Director of Social Impact Analytics
• University Faculty in Data Science or Social Computing
• Data Strategy Consultant for Global Non-Governmental Organizations
• Policy Analyst for Community-Centric Government Initiatives
• Research Scientist in Applied Social Impact Tech
• Ethics and Stewardship Officer for Algorithmic Development
• Important Notices
• The program educates ethical professionals who demonstrate technical excellence, servant leadership, professional integrity, and a commitment to apply sound principles to advance faith-based organizations, strengthen communities, and contribute responsibly.
• HBIU is a lawfully operating nonpublic faith-based postsecondary institution that maintains its status under section 1005.06(1)(f), Florida Statutes. The University annually affirms its compliance with the requirements applicable to faith-based institutions in Florida through Commission for Independent Education.
• HBIU accreditation from QAHE (for quality assurance in pre-tertiary and higher education mechanisms). QAHE offers globally recognized accreditation and quality assurance for higher education, training providers, and professional institutions worldwide. Students should consider the nature and scope of this recognition in relation to their individual certification and professional goals.
• Transfer credit is evaluated individually based on course content, credit hours, grades, institutional documentation, program requirements, and applicable university policies. Although HBIU provides academically structured programs, no institution can guarantee that another college, university, employer, licensing board, or credential-evaluation service will accept its credits or credentials. Students are encouraged to obtain advance written confirmation from the intended receiving organization.
• The program develops academic knowledge and applied competencies for service in faith-based organizations, nonprofit institutions, community programs, and related professional environments. Some occupations associated with the subject area may be regulated by governmental or professional authorities. A degree from HBIU demonstrates completion of the University's academic requirements but does not, by itself, confer professional licensure or legal authority to perform regulated services.
• Where a program is related to an external certification, eligibility is determined exclusively by the applicable certifying organization. Certification bodies may establish additional requirements involving education, examinations, experience, background screening, continuing education, or membership. HBIU does not guarantee certification eligibility or examination approval unless a formal written agreement expressly provides otherwise.
• Career and occupational information is provided to help students make informed educational decisions. Employment outcomes depend on factors such as the graduate's experience, geographic location, professional qualifications, employer requirements, economic conditions, interviewing ability, and any applicable licensure or certification requirements. Completion of a program does not constitute a promise of employment, promotion, job placement, or a particular occupational title.
• This program is delivered through online instruction. Students must have access to the technology, equipment, internet service, software, and learning resources identified in the University's technology requirements.
• Internship or field-experience participation is subject to academic eligibility, site availability, supervisor approval, and the requirements of the participating organization. The University assists students with the placement process but cannot guarantee placement with a particular organization, supervisor, location, or schedule.
• Students are responsible for reviewing the catalog, understanding program requirements, providing accurate information, meeting academic and financial obligations, and verifying whether the program supports their intended educational or professional goals.
• Completion of a University program does not authorize a graduate to use a professional title that is protected or restricted by law. Graduates must use titles that accurately reflect their education, credentials, employment role, and current licensure or certification status.
• Degree abbreviation | Ph.D. in Faith-Based Data Science
• Total program length | 120 semester credit hours
• Maximum approved transfer credit | Up to 40 semester credit hours
• Minimum credits completed through the University after maximum transfer | 80 semester credit hours
• Normal completion time | Four to six academic years, depending on approved transfer credit, enrollment status, research progress, and dissertation completion
• Advanced faith-based data science theory and specialization | 30 credit hours
• Research methods, statistics, and scholarly inquiry | 24 credit hours
• Professional leadership and higher-education teaching | 15 credit hours
• Advanced electives and concentration courses | 18 credit hours
• Scholarly writing and publication | 9 credit hours
• Comprehensive examination and doctoral candidacy | 6 credit hours
• Dissertation research and defense | 18 credit hours
• Total | 120 semester credit hours
• Code | Title | Credits | Prerequisites
• RES700 | Advanced Quantitative Methods | 4 | None
• THE701 | Ethical Reasoning and Digital Stewardship | 3 | None
• RES705 | Research Design and Social Impact | 3 | None
• Code | Title | Credits | Prerequisites
• DAT710 | Machine Learning for Social Good | 4 | RES700
• SOC720 | Data Visualization and Community Narrative | 3 | None
• MGT730 | Data Governance and Leadership | 3 | None
• RES715 | Qualitative Inquiry in Data Science | 3 | None
• Code | Title | Credits | Prerequisites
• DAT740 | Predictive Analytics for Community Resources | 4 | DAT710
• RES750 | Doctoral Research Seminar I | 3 | RES705
• BUS760 | Economic Impact of Social Interventions | 3 | None
• SOC770 | Algorithmic Bias and Social Equity | 3 | None
• Code | Title | Credits | Prerequisites
• RES780 | Doctoral Research Seminar II | 4 | RES750
• DAT790 | Data Privacy and Security for Nonprofits | 3 | None
• MGT810 | Collaborative Leadership in the Data Age | 3 | None
• SOC820 | Sociological Frameworks for Community Development | 3 | None
• Code | Title | Credits | Prerequisites
• RES830 | Advanced Dissertation Research I | 4 | RES780
• DAT840 | Applied Network Analysis for Communities | 3 | None
• BUS850 | Strategic Implementation of Data Strategies | 3 | None
• SOC860 | Global Perspectives in Data for Good | 3 | None
• Code | Title | Credits | Prerequisites
• RES890 | Final Dissertation Defense | 4 | RES830
• RES880 | Advanced Dissertation Research II | 3 | RES830
• COM870 | Public Scholarship and Advocacy | 3 | None
• MIN885 | Formation for Servant Leadership | 3 | None