Dept Industrial Eng & Oper Res
Position Summary
Reporting to the Director of Academic and Student Affairs. The Senior Operations and Data Analyst enables efficient, data-driven management and support of the academic, admissions, career, and operational functions of the Industrial Engineering and Operations Research (IEOR) Department.
Responsibilities
Data Systems, Automation & Applications (30%):
Design, build, and maintain automated tools and scalable workflows to support academic, career, and operational processes across different functional teams within the department.
Develop, optimize, and manage internal databases, data pipelines, and centralized repositories that integrate and synchronize multiple institutional data sources.
Create, deploy, document, and maintain in-house applications and system integrations to streamline cross-functional operations.
Automate recurring administrative and reporting tasks using scripting, macros, APIs, and platform-specific automation tools to improve efficiency and reduce manual errors.
Academic & Admissions Operations Support (30%):
Manage and maintain student and admissions data across internal systems, repositories, and communication platforms, ensuring data integrity and consistency.
Support admissions operations by building, refining, and maintaining queries, reports, dashboards, and tracking tools for application and enrollment management in Slate CRM.
Monitor, audit, and validate data accuracy across systems; investigate discrepancies and implement corrective workflows to maintain compliance and reliability.
Enhance staff workflows by designing structured data tools, templates, and documentation that improve operational transparency and collaboration.
Reporting, Communication & Data Access (20%):
Create, maintain, and automate reports, dashboards, and data visualizations tailored to stakeholders across academic and administrative teams.
Manage large-scale, data-driven communications, including automated mail merges, targeted outreach campaigns, and dynamic distribution lists.
Navigate and integrate emerging data systems and institutional platforms to respond efficiently to complex reporting and analysis requests.
Translate complex datasets and technical findings into clear, structured, and actionable insights for non-technical stakeholders and leadership.
Analytics, Algorithms & Optimization (15%):
Develop analytical models and logic frameworks to support tasks like matching, scheduling, and enrollment management, while identifying conflicts.
Build projection, simulation, and modeling tools to support academic planning.
Analyze historical academic, admissions, and operational data to generate reports, trend analyses, forecasts, and decision-support insights.
Administrative and Events Operations (5%):
Provide on-site support for departmental events, programs, and initiatives as needed.
Offer technical support during events, including setup and troubleshooting of presentation equipment, software, and virtual platforms.
Provide and update content for the Departmental website in the areas of admissions, academic and student affairs, and curricular changes.
Other tasks as needed.
Minimum Qualifications
A bachelor’s degree or equivalent experience is required; graduate-level work is preferred. Minimum of 3–5 years of experience working with data.
Technical Skills: Experience with programming or scripting (Python, JavaScript, macros) and automating tasks.
Data Skills: Experience managing and organizing data, creating reports, and using tools like SQL, Google Sheets, and Excel.
Systems & Integrations: Familiarity with CRMs (Slate preferred), internal tools, and connecting different systems for smooth workflows.
Problem-Solving & Learning: Ability to troubleshoot data or system issues, understand how systems work, and quickly learn new tools.
Professional Strengths: Strong analytical and problem-solving skills; clear communicator with both technical and non-technical audiences; adaptable, collaborative, forward-thinking, and solution-oriented.
Ability to work independently and under pressure, with a high level of attention to detail. Must be able to prioritize multiple tasks with minimal supervision.
Candidates must exercise good judgment and flexibility, with a student-wellness mindset. Positive, mission-oriented, forward-thinking attitude.
Equal Opportunity Employer / Disability / Veteran
Columbia University is committed to the hiring of qualified local residents.
| Title | Location | Department | Summary |
|---|---|---|---|
| Data Analyst | Columbia University Medical Center | Gertrude H. Sergievsky Center | NA |
| Operations and Data Analyst | New York | Dept Industrial Eng & Oper Res | Under general supervision of the Senior Associate Director of Academic and Student Affairs, the Operations and Data Analyst provides operational and technical support for established data systems, reporting, and routine automation used across the academic, admissions, career, and administrative functions of the IEOR Department. Duties vary and the incumbent exercises judgment in selecting appropriate methods to complete assignments, verifying the accuracy of data and outputs, and taking corrective action when needed. Work products (e.g., reports, dashboards, queries, documentation, and data extracts) are relied upon as final source material, with review conducted periodically and/or on a sample basis. The position focuses primarily on maintaining existing systems and reports, executing recurring processes, ensuring data integrity, and responding to department reporting and operational needs. The role collaborates with staff and stakeholders to support consistent use of tools, improve efficiency through incremental enhancements, and escalate complex technical issues as appropriate. |
| Decision Support Research Analyst | New York | Office of Planning & Inst Resh | The Decision Support Research Analyst will work collaboratively with colleagues and stakeholders across the institution to support decision making, drawing insights from quantitative and qualitative analyses. The ideal candidate will have experience in both survey methodology and data analytics. |
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