Job # 042798 Department Code 11001-4406 Department SU Global Job Title Business Data Scientist Location Syracuse, NY Campus Syracuse, NY Commitment to On-Campus Experience Syracuse University is committed to delivering an exceptional student experience through vibrant, engaged campus communities. This position is based at the above campus location and requires regular in-person presence to support our students, collaborate with colleagues, and contribute to our thriving academic environment. Syracuse University values the collaboration, mentorship, and spontaneous connections that happen when our community works together on campus. Remote work arrangements are limited in accordance with University policy. Pay Range $74,000
- $85,000 Pay Determination Pay rates at Syracuse University are based on a combination of factors including, but not limited to, the job responsibilities; the candidate's education, training, work experience and key competencies; the university's strategic priorities; internal peer equity; applicable federal, state, local laws, grant funding and contractual requisites; and external market analyses.
Staff Level S4 FLSA Status Exempt Hours Standard University business hours 8:30am
- 5:00pm (academic year) 8:00am
- 4:30pm (summer) Hours may vary based on operational needs.
This position requires regular on-campus presence and occasional schedule flexibility, including evenings and weekends based on student and operational needs. Job Type Full-time Unionized Position Code Not Applicable Job Description The Business Data Scientist will transform raw data into actionable insights and forward-looking predictions that drive enrollment growth, optimize marketing spend, improve student outcomes, and guide strategic decision-making for this high-growth initiative. This position requires both strong analytical capabilities and advanced data science expertise, including the ability to build predictive models and machine learning algorithms, combined with the business acumen to translate complex findings into clear recommendations for non-technical stakeholders. Reporting to the Executive Director of Operations, this position goes beyond describing what happened — it predicts what comes next. The ideal candidate designs and deploys models that identify at-risk students, forecast enrollment trends, and optimize decisions before problems arise, using data from across the organization including CRM tools, operational systems, marketing platforms, and financial systems. Syracuse University is building something new. We're launching SU Global to reimagine how we support and scale accessible online pathways for non-traditional learners, in a dynamic, innovative, and data-driven environment. That means rethinking how we work. This position requires regular on-campus presence and occasional schedule flexibility, including evenings and weekends based on student and operational needs. Staff operate in a fast-paced, collaborative environment supporting non-traditional learners through an evolving, data-informed model. We're looking for team members who thrive in: High-energy, in-person environments where innovation happens face-to-face Flexible scheduling that follows student needs, not the clock Startup intensity within a world-class university structure We're not looking for people who want a job. We're looking for builders who want a mission. Education and Experience Bachelor's degree required in data science, statistics, machine learning, mathematics, computer science, information systems, or a related quantitative field. Master's degree or PhD strongly preferred. Minimum 3-5 years of experience in data science, advanced analytics, or machine learning roles in high-growth organizations. Demonstrated experience building and deploying predictive models, machine learning algorithms, and statistical models that produce actionable operational outcomes — not just reports. Experience applying data science skills across large, complex datasets in any industry or domain is valued. Experience managing multiple concurrent projects in fast-paced environments. Skills and Knowledge Data Science & Machine Learning (Required) Proficiency in Python or R for data science, statistical modeling, and machine learning Experience building supervised and unsupervised models: classification, regression, clustering, survival analysis Hands-on experience with predictive modeling frameworks (scikit-learn, XGBoost, or equivalent) Understanding of causal inference, A/B testing, and experimental design Ability to validate, tune, and communicate model performance metrics (AUC, precision/recall, RMSE, etc.) Technical Proficiency Advanced SQL for data extraction, transformation, and manipulation Advanced Excel including pivot tables, formulas, and statistical functions Expert proficiency with Tableau and/or Power BI for visualization and dashboard development Familiarity with CRM systems, student or customer information systems, and marketing analytics platforms; experience with enterprise SIS or ERP platforms a plus Understanding of web analytics, survey tools, and data warehousing concepts Analytical & Problem-Solving Highly analytical mindset to identify patterns, trends, and causal relationships in complex datasets Strategic thinking to connect predictive insights to business strategy and operational action Critical thinking to evaluate data quality, select appropriate analytical approaches, and communicate model limitations honestly Communication & Collaboration Excellent communication skills to explain predictive models and complex concepts to non-technical audiences Strong data storytelling capabilities — translating model outputs into narratives stakeholders can act on Collaborative work style with demonstrated ability to build relationships across organizational boundaries Domain Adaptability & Context Demonstrated ability to apply data science skills across industries or data domains; no specific sector experience required Comfort working within complex, multi-stakeholder organizations where data informs decisions across multiple functions Willingness to quickly learn domain-specific context, including student lifecycle, enrollment funnels, and operational workflows, on the job Knowledge of FERPA compliance and ethical data practices a plus; experience with data governance frameworks in any regulated industry is equally relevant Responsibilities Predictive Modeling & Data Science Design, build, and deploy predictive models and machine learning algorithms that generate forward-looking insights — not just retrospective reporting. Develop models that identify which current students are at-risk for non-persistence based on causal variables correlated with retention. Build enrollment forecasting models that project future trends, conversion probabilities, and revenue scenarios with quantified confidence levels. Create segmentation and clustering models to identify distinct student populations, behavioral patterns, and intervention targets. Develop attribution and causal inference models to measure the true impact of marketing campaigns, interventions, and program changes. Partner with enrollment, student success, and marketing teams to deploy models in operational workflows, ensuring predictions drive real-time decisions. Document model methodology, assumptions, validation approaches, and performance metrics to ensure reproducibility, transparency, and compliance with FERPA and institutional data governance standards. Descriptive Analytics & Strategic Insights Aggregate and synthesize data from multiple sources — including enterprise data systems, CRM, LMS, marketing automation tools, web analytics, and data warehouses — to identify trends, anomalies, opportunities, and risks. Conduct cohort analyses, funnel analyses, segmentation studies, and comparative assessments to understand program performance, student behavior, and competitive positioning. Translate analytical findings into clear narratives that connect data insights to business implications and recommended actions for executives, program directors, enrollment teams, and operational staff. Provide evidence-based recommendations that are grounded in both descriptive analysis and predictive science. Performance Measurement, KPIs & Dashboards Establish and maintain KPIs aligned with SU Global strategic objectives including enrollment targets, conversion metrics, student success measures, financial performance, and operational efficiency. Develop comprehensive dashboards and automated reporting systems using Tableau, Power BI, or similar tools that provide real-time visibility into critical metrics. Integrate model outputs into dashboards so stakeholders can act on predictions, not just historical data. Monitor data quality and integrity across source systems, identifying and resolving discrepancies and establishing validation protocols. Build self-service reporting capabilities that empower teams to access relevant data independently while maintaining governance and consistency. Cross-Functional Collaboration & Process Improvement Work collaboratively across SU Global functions including enrollment, marketing, student success, finance, operations, and academic programs to understand data needs, align on priorities, and deliver analytical and predictive support. Partner with University central offices including Institutional Research, Registrar's Office, Enterprise Analytics, Enrollment Management, and IT to leverage existing data resources and ensure compliance with governance standards. Identify opportunities to enhance data collection, improve system integrations, automate manual processes, and build scalable data science infrastructure as SU Global grows. Lead meetings to review performance trends, model results, and analytical findings to build organizational capacity for evidence-based, predictive decision-making. Other Duties as Assigned Support special projects, ad hoc analyses, and emerging priorities as SU Global scales and evolves. Physical Requirements Not Applicable Tools/Equipment Not Applicable Application Instructions In addition to completing an online application, please attach a resume and cover letter. About Syracuse University Syracuse University is a private, international research university with distinctive academics, diversely unique offerings, and an undeniable spirit. Located in the geographic heart of New York State, with a global footprint, and over 150 years of history, Syracuse University offers a quintessential college experience. The scope of Syracuse University is a testament to its strengths: a pioneering history dating back to 1870; a choice of more than 200 majors, 100 minors, and 200 advanced degree programs offered across the University's 13 schools and colleges; over 15,000 undergraduates and over 6,000 graduate students; more than a quarter of a million alumni in 160 countries; and a student population from all 50 U.S. states and 123 countries. For more information, please visit http://www.syracuse.edu. About the Syracuse area Syracuse is a medium-sized city situated in the geographic center of New York State approximately 250 miles northwest of New York City. The metro-area population totals approximately 500,000. The area offers a low cost of living and provides many social, cultural, and recreational options, including parks, museums, festivals, professional regional theater, and premier shopping venues. Syracuse and Central New York present a wide range of seasonal recreation and attractions ranging from water skiing and snow skiing, hiking in the Adirondacks, touring the historic sites, visiting wineries along the Finger Lakes, and biking on trails along the Erie Canal. EEO Statement Syracuse University is an equal-opportunity institution. The University prohibits discrimination and harassment based on race, color, creed, religion, sex, gender, national origin, citizenship, ethnicity, marital status, age, disability, sexual orientation, gender identity and gender expression, veteran status, or any other status protected by applicable law to the extent prohibited by law. This nondiscrimination policy covers admissions, employment, and access to and treatment in University programs, services, and activities. Commitment to Supporting and Hiring Veterans Syracuse University has a long history of engaging veterans and the military-connected community through its educational programs, community outreach, and employment programs. After World War II, Syracuse University welcomed more than 10,000 returning veterans to our campus, and those veterans literally transformed Syracuse University into the national research institution it is today. The University's contemporary commitment to veterans builds on this historical legacy, and extends to both class-leading initiatives focused on making an SU degree accessible and affordable to the post-9/11 generation of veterans, and also programs designed to position Syracuse University as the employer of choice for military veterans, members of the Guard and Reserve, and military family members. Commitment to a Respectful and Welcoming Community Syracuse University fosters a welcoming learning environment where students, faculty, administrators, staff, curriculum, social activities, governance, and all aspects of campus life reflect a broad range of perspectives and experiences. The University community values the many similarities and differences among individuals and groups. At Syracuse, we are committed to preparing students to engage with and appreciate the richness of backgrounds, beliefs, and experiences that shape our society. To achieve this, we strive to cultivate a community that respects and encourages open dialogue, understanding, and mutual respect. Business Data Scientist 4.3 4.3 out of 5 stars Syracuse, NY $74,000
- $85,000 a year
- Full-time Syracuse University 733 reviews $74,000
- $85,000 a year
- Full-time Job # 042798 Department Code 11001-4406 Department SU Global Job Title Business Data Scientist Location Syracuse, NY Campus Syracuse, NY Commitment to On-Campus Experience Syracuse University is committed to delivering an exceptional student experience through vibrant, engaged campus communities.
This position is based at the above campus location and requires regular in-person presence to support our students, collaborate with colleagues, and contribute to our thriving academic environment. Syracuse University values the collaboration, mentorship, and spontaneous connections that happen when our community works together on campus. Remote work arrangements are limited in accordance with University policy. Pay Range $74,000
- $85,000 Pay Determination Pay rates at Syracuse University are based on a combination of factors including, but not limited to, the job responsibilities; the candidate's education, training, work experience and key competencies; the university's strategic priorities; internal peer equity; applicable federal, state, local laws, grant funding and contractual requisites; and external market analyses.
Staff Level S4 FLSA Status Exempt Hours Standard University business hours 8:30am
- 5:00pm (academic year) 8:00am
- 4:30pm (summer) Hours may vary based on operational needs.
This position requires regular on-campus presence and occasional schedule flexibility, including evenings and weekends based on student and operational needs. Job Type Full-time Unionized Position Code Not Applicable Job Description The Business Data Scientist will transform raw data into actionable insights and forward-looking predictions that drive enrollment growth, optimize marketing spend, improve student outcomes, and guide strategic decision-making for this high-growth initiative. This position requires both strong analytical capabilities and advanced data science expertise, including the ability to build predictive models and machine learning algorithms, combined with the business acumen to translate complex findings into clear recommendations for non-technical stakeholders. Reporting to the Executive Director of Operations, this position goes beyond describing what happened — it predicts what comes next. The ideal candidate designs and deploys models that identify at-risk students, forecast enrollment trends, and optimize decisions before problems arise, using data from across the organization including CRM tools, operational systems, marketing platforms, and financial systems. Syracuse University is building something new. We're launching SU Global to reimagine how we support and scale accessible online pathways for non-traditional learners, in a dynamic, innovative, and data-driven environment. That means rethinking how we work. This position requires regular on-campus presence and occasional schedule flexibility, including evenings and weekends based on student and operational needs. Staff operate in a fast-paced, collaborative environment supporting non-traditional learners through an evolving, data-informed model. We're looking for team members who thrive in: High-energy, in-person environments where innovation happens face-to-face Flexible scheduling that follows student needs, not the clock Startup intensity within a world-class university structure We're not looking for people who want a job. We're looking for builders who want a mission. Education and Experience Bachelor's degree required in data science, statistics, machine learning, mathematics, computer science, information systems, or a related quantitative field. Master's degree or PhD strongly preferred. Minimum 3-5 years of experience in data science, advanced analytics, or machine learning roles in high-growth organizations. Demonstrated experience building and deploying predictive models, machine learning algorithms, and statistical models that produce actionable operational outcomes — not just reports. Experience applying data science skills across large, complex datasets in any industry or domain is valued. Experience managing multiple concurrent projects in fast-paced environments. Skills and Knowledge Data Science & Machine Learning (Required) Proficiency in Python or R for data science, statistical modeling, and machine learning Experience building supervised and unsupervised models: classification, regression, clustering, survival analysis Hands-on experience with predictive modeling frameworks (scikit-learn, XGBoost, or equivalent) Understanding of causal inference, A/B testing, and experimental design Ability to validate, tune, and communicate model performance metrics (AUC, precision/recall, RMSE, etc.) Technical Proficiency Advanced SQL for data extraction, transformation, and manipulation Advanced Excel including pivot tables, formulas, and statistical functions Expert proficiency with Tableau and/or Power BI for visualization and dashboard development Familiarity with CRM systems, student or customer information systems, and marketing analytics platforms; experience with enterprise SIS or ERP platforms a plus Understanding of web analytics, survey tools, and data warehousing concepts Analytical & Problem-Solving Highly analytical mindset to identify patterns, trends, and causal relationships in complex datasets Strategic thinking to connect predictive insights to business strategy and operational action Critical thinking to evaluate data quality, select appropriate analytical approaches, and communicate model limitations honestly Communication & Collaboration Excellent communication skills to explain predictive models and complex concepts to non-technical audiences Strong data storytelling capabilities — translating model outputs into narratives stakeholders can act on Collaborative work style with demonstrated ability to build relationships across organizational boundaries Domain Adaptability & Context Demonstrated ability to apply data science skills across industries or data domains; no specific sector experience required Comfort working within complex, multi-stakeholder organizations where data informs decisions across multiple functions Willingness to quickly learn domain-specific context, including student lifecycle, enrollment funnels, and operational workflows, on the job Knowledge of FERPA compliance and ethical data practices a plus; experience with data governance frameworks in any regulated industry is equally relevant Responsibilities Predictive Modeling & Data Science Design, build, and deploy predictive models and machine learning algorithms that generate forward-looking insights — not just retrospective reporting. Develop models that identify which current students are at-risk for non-persistence based on causal variables correlated with retention. Build enrollment forecasting models that project future trends, conversion probabilities, and revenue scenarios with quantified confidence levels. Create segmentation and clustering models to identify distinct student populations, behavioral patterns, and intervention targets. Develop attribution and causal inference models to measure the true impact of marketing campaigns, interventions, and program changes. Partner with enrollment, student success, and marketing teams to deploy models in operational workflows, ensuring predictions drive real-time decisions. Document model methodology, assumptions, validation approaches, and performance metrics to ensure reproducibility, transparency, and compliance with FERPA and institutional data governance standards. Descriptive Analytics & Strategic Insights Aggregate and synthesize data from multiple sources — including enterprise data systems, CRM, LMS, marketing automation tools, web analytics, and data warehouses — to identify trends, anomalies, opportunities, and risks. Conduct cohort analyses, funnel analyses, segmentation studies, and comparative assessments to understand program performance, student behavior, and competitive positioning. Translate analytical findings into clear narratives that connect data insights to business implications and recommended actions for executives, program directors, enrollment teams, and operational staff. Provide evidence-based recommendations that are grounded in both descriptive analysis and predictive science. Performance Measurement, KPIs & Dashboards Establish and maintain KPIs aligned with SU Global strategic objectives including enrollment targets, conversion metrics, student success measures, financial performance, and operational efficiency. Develop comprehensive dashboards and automated reporting systems using Tableau, Power BI, or similar tools that provide real-time visibility into critical metrics. Integrate model outputs into dashboards so stakeholders can act on predictions, not just historical data. Monitor data quality and integrity across source systems, identifying and resolving discrepancies and establishing validation protocols. Build self-service reporting capabilities that empower teams to access relevant data independently while maintaining governance and consistency. Cross-Functional Collaboration & Process Improvement Work collaboratively across SU Global functions including enrollment, marketing, student success, finance, operations, and academic programs to understand data needs, align on priorities, and deliver analytical and predictive support. Partner with University central offices including Institutional Research, Registrar's Office, Enterprise Analytics, Enrollment Management, and IT to leverage existing data resources and ensure compliance with governance standards. Identify opportunities to enhance data collection, improve system integrations, automate manual processes, and build scalable data science infrastructure as SU Global grows. Lead meetings to review performance trends, model results, and analytical findings to build organizational capacity for evidence-based, predictive decision-making. Other Duties as Assigned Support special projects, ad hoc analyses, and emerging priorities as SU Global scales and evolves. Physical Requirements Not Applicable Tools/Equipment Not Applicable Application Instructions In addition to completing an online application, please attach a resume and cover letter. About Syracuse University Syracuse University is a private, international research university with distinctive academics, diversely unique offerings, and an undeniable spirit. Located in the geographic heart of New York State, with a global footprint, and over 150 years of history, Syracuse University offers a quintessential college experience. The scope of Syracuse University is a testament to its strengths: a pioneering history dating back to 1870; a choice of more than 200 majors, 100 minors, and 200 advanced degree programs offered across the University's 13 schools and colleges; over 15,000 undergraduates and over 6,000 graduate students; more than a quarter of a million alumni in 160 countries; and a student population from all 50 U.S. states and 123 countries. For more information, please visit http://www.syracuse.edu. About the Syracuse area Syracuse is a medium-sized city situated in the geographic center of New York State approximately 250 miles northwest of New York City. The metro-area population totals approximately 500,000. The area offers a low cost of living and provides many social, cultural, and recreational options, including parks, museums, festivals, professional regional theater, and premier shopping venues. Syracuse and Central New York present a wide range of seasonal recreation and attractions ranging from water skiing and snow skiing, hiking in the Adirondacks, touring the historic sites, visiting wineries along the Finger Lakes, and biking on trails along the Erie Canal. EEO Statement Syracuse University is an equal-opportunity institution. The University prohibits discrimination and harassment based on race, color, creed, religion, sex, gender, national origin, citizenship, ethnicity, marital status, age, disability, sexual orientation, gender identity and gender expression, veteran status, or any other status protected by applicable law to the extent prohibited by law. This nondiscrimination policy covers admissions, employment, and access to and treatment in University programs, services, and activities. Commitment to Supporting and Hiring Veterans Syracuse University has a long history of engaging veterans and the military-connected community through its educational programs, community outreach, and employment programs. After World War II, Syracuse University welcomed more than 10,000 returning veterans to our campus, and those veterans literally transformed Syracuse University into the national research institution it is today. The University's contemporary commitment to veterans builds on this historical legacy, and extends to both class-leading initiatives focused on making an SU degree accessible and affordable to the post-9/11 generation of veterans, and also programs designed to position Syracuse University as the employer of choice for military veterans, members of the Guard and Reserve, and military family members. Commitment to a Respectful and Welcoming Community Syracuse University fosters a welcoming learning environment where students, faculty, administrators, staff, curriculum, social activities, governance, and all aspects of campus life reflect a broad range of perspectives and experiences. The University community values the many similarities and differences among individuals and groups. At Syracuse, we are committed to preparing students to engage with and appreciate the richness of backgrounds, beliefs, and experiences that shape our society. To achieve this, we strive to cultivate a community that respects and encourages open dialogue, understanding, and mutual respect.
