Data & Intelligence Analyst, CMC

Department: Kellogg Career Management Ctr

Salary/Grade: EXS/9

Job Summary:

This role independently manages the full lifecycle of Kellogg’s career outcomes data and ensures the accuracy, integrity, consistency, and timely presentation and delivery of official reports to senior stakeholders. This role is the primary administrator for the Career Management System for a dynamic graduate business school, serving 2,300 students across nine distinct academic programs annually. Manages the configuration, troubleshooting, integrations and reporting workflows for the system.

This role oversees and implements data standards, ensures compliance, and maintains technical and training documentation, and leads data engineering activities that support automation, validation, and reliable data pipelines. In consultation with other stakeholders, serves as the data and systems expert for the system of record and its data.

The position supports survey administration, data collection, and advanced analytics, and collaborates with teams across the Career Management Center and institutional partners to deliver high‑quality insights and contribute to strategic initiatives. Using analysis and development tools such as Python, SQL, and Power BI, the role integrates and synthesizes data from multiple enterprise systems to produce dashboards, analytical products, and insights to inform operational and strategic decisions with predictive analytics.

The role requires strong data storytelling, presentation and communication skills to translate stakeholder questions into complex data and analyses, and disseminate clear, actionable information for stakeholders.

This role requires close partnership with technical, analytical, and operational stakeholders across the Career Management Center and the institution, relying on strong communication and collaboration to deliver high-quality insights. The position emphasizes reproducible, audit-ready analytical practices and requires rigorous documentation to ensure transparency, continuity, and long-term data stewardship. Success in this role depends on strong collaborative partnerships with these teams to translate complex data needs into reliable analytical outputs.

\*Note: Not all aspects of the job are covered by this job description.

Specific Responsibilities:

Data Architecture, Engineering & Analytics

Design, build, and maintain scalable data pipelines integrating 12Twenty (CMS), survey platforms, and university enterprise systems using Python and SQL.

Architect automated, version-controlled analytics workflows that ensure reproducibility, auditability, and transparency across the full data lifecycle.

Develop production-ready reproducible analytical products using R Markdown, Quarto, and Jupyter to support reporting automation, scenario modeling, and sensitivity analysis. Write modular, maintainable scripts and software programs to ingest, transform, model, and visualize structured and unstructured data.

Engineer robust data validation frameworks, including schema enforcement, anomaly detection, cross-system reconciliation, and automated quality monitoring.

Maintain comprehensive technical artifacts including data dictionaries, lineage documentation, code repositories, model documentation, and system specifications.

Partner with institutional IT and technical stakeholders to ensure secure integrations, system reliability, and scalable data infrastructure.

Data Science

Lead the end-to-end analytical lifecycle for the Career Management Center: problem framing, data acquisition, feature engineering, modeling, validation, and stakeholder delivery.

Administer and validate surveys, applying rigorous statistical controls to ensure definitional integrity, comparability, and longitudinal consistency.

Conduct advanced exploratory, diagnostic, and inferential analyses on a variety of dynamic metrics, reviewing for optimization and identifying trends.

Apply statistical modeling, classification techniques, regression frameworks, and longitudinal methods to uncover performance and outcome drivers.

Partner with cross-functional teams to translate analytical insights into evidence-based operational and strategic decisions.

Communicate complex quantitative findings through compelling data storytelling, visual analytics, and executive-ready presentations tailored to technical and non-technical audiences.

Institutional Reporting & Rankings Strategy

Develop and manage official employment outcome analytical products, including automated publications, interactive dashboards, intelligence summaries, and longitudinal performance analyses.

Design executive-facing dashboards and decision-support tools that integrate predictive insights and trend intelligence.

Lead the analytical infrastructure supporting rankings submissions and accreditation reporting; build sustainable processes and validation controls to ensure methodological consistency. Prepare statistically validated, fully documented data submissions for ranking organizations and accrediting bodies in accordance with CSEA and institutional standards.

Serve as an analytics lead for internal and external data inquiries, delivering accurate, comparable, and context-rich analyses in a timely manner.

Maintain structured, version-controlled archives of methodologies, ranking submissions, historical analyses, and model documentation.

Predictive Analytics & Data Modeling

Design and deploy predictive models for key metrics.

Apply advanced statistical and machine learning approaches (e.g., survival analysis, longitudinal modeling, regression, clustering) to evaluate recruiting dynamics and outcome drivers.

Implement model validation, performance monitoring, recalibration, and documentation practices consistent with responsible model governance.

Present predictive insights and strategic forecasts to leadership, clearly articulating assumptions, uncertainty, limitations, and actionable implications.

Establish and advance a forward-looking analytics roadmap that elevates CMC’s capabilities in predictive and prescriptive decision support.

Systems Administration

Serve as the CMS systems owner and subject-matter expert, overseeing configuration, integrations, workflow architecture, and reporting logic.

Implement system-level data governance controls and internal reporting validation mechanisms.

Troubleshoot system issues, optimize data structures, and coordinate technical resolutions with vendor and university partners.

Develop standardized, automated extracts and reporting frameworks that support strategic and operational needs.

Author and present both technical and non-technical documentation of data models, analytical methodologies, and system workflows.

Data Governance, Standards & Compliance

Ensure strict adherence to CSEA and other industry reporting standards through documented methodologies and controlled processes.

Maintain and evolve official Methods & Definitions documentation to ensure clarity, defensibility, and longitudinal consistency. Translate evolving reporting standards into implemented validation logic, data controls, and reproducible workflows.

Maintain audit trails, QA protocols, and version-controlled processes and documentation.

Partner with institutional stakeholders to align analytics practices with university data governance, privacy, and security frameworks.

Miscellaneous

Performs other duties as assigned.

Minimum Qualifications (Education, Experience, Certifications, Skills)

Bachelor’s degree in a quantitative field

4+ years of experience in data analytics/data science

Advanced proficiency in Python and SQL

Experience designing and maintaining data pipelines and structured reporting processes that ensure data integrity, reproducibility, and auditability.

Strong foundation in statistical analysis, predictive modeling (including risk classification and longitudinal analysis), and data validation methodologies.

Experience developing reports, dashboards, and data visualizations using business intelligence tools (e.g., Power BI, Tableau, or Cognos BI) to support executive decision-making.

Experience developing reproducible analytical workflows using tools such as R Markdown, Quarto, or Jupyter

Demonstrated ability to translate complex analytical findings into clear, actionable insights for non-technical stakeholders.

Strong project management skills with the ability to manage multiple priorities independently in a deadline-driven environment.

Excellent written and verbal communication skills, including the ability to present analytical findings effectively to diverse audiences.

Preferred Qualifications (Education, Experience, Certifications, Skills)

Experience working in cloud-based data environments (e.g., Azure) and using version control systems (e.g., Git)

Experience in higher education, career services analytics, or institutional research

Familiarity with employment outcomes reporting standards (e.g., CSEA) and experience supporting institutional reporting.

Experience administering CRM or career management systems (e.g., 12Twenty) and supporting related data governance practices.

Target hiring range for this position will be $95,000 - $105,000 per year. Offered salary will be determined by the applicant’s education, experience, knowledge, skills and abilities, as well as internal equity and alignment with market data.

Benefits:

At Northwestern, we are proud to provide meaningful and competitive benefits. The available benefits package for this position will include health, dental, vision, disability, and life insurance; paid vacation and holidays; paid medical/sick and parental leave; tuition benefits for the employee and dependents; pre-tax and flex spending accounts for commuting and dependent care; generous retirement savings options; and wellness programs.

For a comprehensive overview of available benefits, including eligibility details, visit us at https://www.northwestern.edu/hr/benefits/index.html to learn more.

Work-Life and Wellness:

Northwestern offers comprehensive programs and services to help you and your family navigate life’s challenges and opportunities and adopt and maintain healthy lifestyles.

We support flexible work arrangements where possible and programs to help you locate and pay for quality, affordable childcare and senior/adult care. Visit us at https://www.northwestern.edu/hr/benefits/work-life/index.html to learn more.

Professional Growth & Development:

Northwestern supports employee career development in all circumstances whether your workspace is on campus or at home. If you’re interested in developing your professional potential or continuing your formal education, we offer a variety of tools and resources. Visit us at https://www.northwestern.edu/hr/learning/index.html to learn more.

Northwestern University is an Equal Opportunity Employer and does not discriminate on the basis of protected characteristics, including disability and veteran status. View Northwestern’s non-discrimination statement. Job applicants who wish to request an accommodation in the application or hiring process should contact the Office of Civil Rights and Title IX Compliance. View additional information on the accommodations process.

#LI-AS1

• Bachelor’s degree in a quantitative field and 4+ years of data analytics/data science experience
• Advanced proficiency in Python, SQL, and experience designing data pipelines ensuring integrity and reproducibility
• Strong skills in statistical analysis, predictive modeling, BI tools (Power BI, Tableau), and translating complex data for non-technical audiences