Data Scientist
Position Summary
The Office of Institutional Data, Evaluation, Analytics, and Strategy (IDEAS) seeks a versatile data professional who translates advanced analytics and predictive modeling into scalable, actionable solutions for campus partners. Working under the guidance of the Director of the Sallyport Fellows Program and the Lead Data Scientist within IDEAS, the Data Scientist serves as an advanced analytics resource embedded within the Institutional Research and Analytics team. While housed in IDEAS, this position works in close collaboration with the Division of Student Life and Undergraduate Education and the Sallyport Fellows Program, applying predictive and statistical modeling to address complex research questions relevant to undergraduate student success and fellowship initiatives. This role is responsible for building sustainable, accurate data sources and developing scalable analytical solutions that directly inform strategies and decisions within these partner units. Additionally, the Data Scientist contributes to promoting reproducible research methodologies and a consistent advanced analytics framework across the team, leveraging domain expertise in higher education to deliver impactful, data-driven insights.
About the Role
This position is offered as a hybrid role, combining both in-office and remote work to provide flexibility and support collaboration. Occasional work-related travel is expected. For the right candidate, this could be a hybrid position, with the expectation of at least 3 days working from the office during Fall and Spring terms, with working hours remaining standard Central Time.
Special Instructions To Applicants
To apply, all interested applicants should attach a resume and cover letter in the Supporting Documents section of the application, preferably in PDF format. Your materials should demonstrate your knowledge, skills, and experience in translating complex business needs into technical solutions using advanced analytics, including predictive modeling and statistical analysis, to drive institutional decision-making. Applicants must be legally authorized to work in the United States at the time of hire and must not require employment visa sponsorship now or in the future.
Minimum Requirements
- Bachelor’s degree in a relevant field (data science, statistics, social sciences, or related field)
- Minimum of 4+ years of professional work experience in data management, data science, or analytical solution development
- Master’s degree in a relevant field (data science, statistics, social sciences, or related field) is preferred
Skills
- Solution Translation: Demonstrated ability to partner with diverse stakeholders to translate complex business needs into clear technical specifications, analytical approaches, and decision-ready deliverables
- Advanced Analytics and Modeling: Proficiency in Python and/or R to conduct advanced statistical and predictive modeling (e.g., regression, classification, clustering, forecasting)
- Data Management: Advanced experience querying and transforming data within centralized enterprise data platforms, including strong SQL proficiency
- Analytic Development and Data Communication: Experience developing enterprise-scale dashboards (e.g., Tableau) and communicating complex findings through clear data visualization and narrative storytelling to executive audiences
Essential Functions
- Stakeholder Consultation & Solution Design (30%): Partners with campus leadership and subject matter experts to define analytical needs and clarify research questions. Independently determines appropriate analytical methodologies, modeling approaches, and data presentation strategies to deliver actionable solutions.
- Advanced Analytics & Modeling (30%): Designs and implements advanced statistical and predictive modeling approaches to address complex institutional questions. Applies appropriate modeling techniques, ensuring that models are interpretable, well-documented, and decision-relevant.
- Sustainable Data Development (20%): Designs and maintains scalable, reliable data pipelines and analytical workflows that support both descriptive reporting and predictive modeling. Automates data preparation and validation processes to ensure accuracy, reproducibility, and long-term sustainability.
- Technical Mentorship (15%): Guides the continued evolution of the team’s advanced analytics practice. Promotes reproducible research standards and supports the expansion of predictive and prescriptive analytical capabilities.
- Documentation & Quality Assurance (5%): Develops comprehensive technical documentation and ensures analytical products meet institutional standards for data governance, accuracy, transparency, and reproducibility.
Additional Functions
- Contributes to special projects and emerging priorities as needed to advance departmental and institutional goals.
- Duties may expand or shift in alignment with strategic initiatives.
- Performs other duties as assigned to support departmental and institutional priorities.
Rice University HR | Benefits
Rice University HR | Benefits