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.

Special Instructions to Applicants

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.

Ideal Candidate Statement

The ideal candidate operates comfortably at the intersection of stakeholder partnership and advanced analytics. You combine strong technical execution with the ability to translate complex institutional needs into rigorous, reproducible analytical solutions using Python, R, and/or SQL. You have substantial experience with best practices in data collection and management, understand the interconnected nature of admissions, student, HR, research, and finance data, and can apply advanced statistical and predictive modeling techniques to deepen and extend existing reporting and analytical practices. As a mentor and technical leader, you will help the team broaden its analytical toolkit—building on a strong foundation of descriptive analysis to incorporate predictive and prescriptive approaches that inform institutional strategy.

Workplace Requirements

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. Per Rice policy 440 , work arrangements may be subject to change.

Hiring Range: $110,000-$120,000 annually (commensurate with experience)

*Exempt (salaried) positions under FLSA are not eligible for overtime.

This position is funded by a grant, soft and/or restricted funds. Continued employment is contingent on the renewal of funding.

Minimum Requirements

• Bachelor’s degree in a relevant field (data science, statistics, social sciences, or related field)
  • In lieu of the education requirement, additional related experience, above and beyond what is required, may be substituted on an equivalent year-for-year basis.
• Minimum of 4+ years of professional work experience in data management, data science, or analytical solution development
  • In lieu of the experience requirement, additional related education above and beyond what is required may be substituted on an equivalent year-for-year basis.
• 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). Ability to select and apply appropriate methodologies to solve institutional research questions
  • 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

Preferences

• Master’s degree in a relevant field (data science, statistics, social sciences, or related field)
• Minimum of 5+ years of professional work experience in data management, data science, or analytical solution development
• Experience in higher education or similarly complex institutional environments.
• Experience working with student lifecycle, student administration data systems, and undergraduate student data
Doctoral degree is preferred

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

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Rice University is committed to ensuring Equal Employment Opportunity and welcoming the fullness of diversity into our candidate pools. Rice considers qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national or ethnic origin, genetic information, disability, or protected veteran status. Rice also provides reasonable accommodations to qualified persons with disabilities. If an applicant requires a reasonable accommodation for any part of the application or hiring process, please get in touch with Rice University’s Human Resources Office via email at View email address on us.fitly.work for support.

If you have any additional questions, please email us at ***email_hidden*** . Thank you for your interest in employment with Rice University.