Princeton University

Overview Under the direction of the Manager of Life Safety Technology Service, the Analyst oversees the administration, deployment, and support of applications within the Facilities Technology portfolio. This role collaborates closely with Facilities, university departments, and external partners to deliver innovative technical solutions that enhance operational efficiency and service delivery. The technical analyst leads cross-functional projects, translates business needs into scalable system designs, and ensures the reliability, security, and usability of facilities applications. Success in this role requires technical acumen, strategic coordination, and a commitment to continuous improvement across a diverse range of systems and stakeholders. Responsibilities Technical & System Administration & Support (35%) Provide server-level administration for applications in production and test environments, including setup and review of performance monitoring and alerts, firewall rules, system configurations and access Test monthly operating system (OS) and SQL patching, in coordination with IT partners. Remediate critical and severe OS, middleware, application, and firmware vulnerabilities identified. Monitor application platform for abnormalities; verify the integrity and availability of all servers, systems, network, and key processes. Review system and application logs to identify potential problems; troubleshoot and resolve technical application issues. Administer applications in production and test environments, including system configurations and user access. Monitor system performance and integrity; troubleshoot and resolve technical issues across facilities platforms. Conduct system testing and oversee vendor-led enhancements, updates, and modifications. Plan and execute functional and user acceptance testing, including test script development and validation. Ensure accurate data integration between Facilities and university systems. Support organizational readiness by contributing to training materials and communication strategies for new capabilities. Provide technical direction to vendors and consultants, maintaining service level agreements. Partner with the Office of Information Technology to leverage shared infrastructure, network, and security services. Respond to after-hours emergencies and incidents as needed. Project Leadership & Process Optimization (40%) Lead projects related to application onboarding, upgrades, and enhancements. Document and analyze functional requirements; identify gaps and recommend scalable solutions. Collaborate with business owners to translate needs into reliable, efficient technical specifications. Reconcile processes across facilities applications and communicate downstream impacts. Coordinate with OIT and external vendors to address technical requirements and ensure cohesive solution design. Promote inclusion and ownership in solution development and implementation. Apply modern tools and methods to improve application usability and performance. Demonstrate persistence and skill in gathering relevant information from diverse sources. Stakeholder Engagement & Strategic Communication (25%) Build and maintain effective relationships with stakeholders across campus. Facilitate alignment meetings, issue resolution, and prioritization discussions. Communicate clearly and succinctly across technical and non-technical audiences. Evaluate and reconcile information from multiple sources to identify true business needs. Create and deliver technical documentation, workflows, and training materials. Manage concurrent projects and production support items with sound judgment and minimal oversight. Stay current on emerging technologies and recommend cost-effective, user-friendly solutions. Qualifications 5+ years related work experience with 3+ years leading technical oversight of 3rd party applications including server administration of OS, middleware, firewall rules and network connectivity. Demonstrated experience providing technical governance of 3rd party applications including break/fix, vulnerability remediation, monitoring and performance, stability, and routine Experience with server operating systems, Windows (R2022 and up), or Linux (OpenSUSE and Red Hat) and databases (SQL Server 2019 and up and Oracle 19c). Basic proficiency with programming languages SQL and PowerShell used to develop automation scripts and routine tasks. Hands on experience in troubleshooting and remediation of break/fix and security or other vulnerabilities identified through system monitoring and alerts. Experience managing application integrations using tools such as ODBC, SDK and APIs. Proven experience supporting third-party applications, including upgrades and integrations Proficiency with facilities-related systems (e.g., video surveillance, electronic card access, fire alarm monitoring) Experience with SQL, scripting, and data interface validation Strong understanding of system testing, UAT, and release management Familiarity with IT service management frameworks (e.g., ITIL) Demonstrated project management skills and cross-functional collaboration Excellent written and verbal communication, including documentation and training Ability to work independently and solve complex problems with minimal oversight High attention to detail, quality, and accuracy Strong critical thinking and stakeholder engagement skills Experience designing and implementing training and change management strategies Ability to evaluate emerging technologies and recommend scalable solutions Bachelor's degree in information technology, Computer Science, or related experience Preferred Qualifications Experience with life safety systems such as CCURE 9000, Milestone, Salto, True Site Workstation, or other video surveillance, electronic card access, and fire alarm monitoring platforms Proficiency with IT service platforms (e.g., ServiceNow, JIRA, Zendesk) Certifications such as ITIL, PMP, or life safety security industry certifications Experience with business intelligence tools (e.g., Cognos, Tableau, Power BI) Prior experience in higher education or large institutional environments Knowledge of life safety data analytics Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly. If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information. PI154ab8d36e73-1838

Overview The Director, Data Governance and Security is a member of the Data Strategy & Innovation team within University Advancement. Data Strategy & Innovation is dedicated to housing, managing, analyzing, and disseminating information and data to inform Advancement strategy, foster strong relationships with donors, volunteers, and campus partners, and promote effective integration. Reporting to the Associate Vice President for Data Strategy & Innovation, the Director will be responsible for supporting University Advancement's engagement efforts and overseeing an enterprise-wide role-based approach to data access through data governance, data management, and data security policies and practices. This job requires initiative, critical judgment, discretion, and strong technical, writing, and communications skills. Responsibilities Data Governance Manage a transparent and consistent approach to role-based access to alumni and donor data within Advancement systems. Develop and maintain policies for the governance and management of data access. This includes the timely update of all confidentiality agreement and related documents, and issuing and tracking of signoff by relevant constituencies. Work closely with OGC to confirm relevance, accuracy and applicability to all process related forms and documents. Maintain roles and responsibilities related to data access and ensure clear accountability for stewardship of Advancement's alumni data. Oversee internal process and identify process improvements for administering access to alumni and donor data, ensuring requests are addressed in a timely and efficient manner. Maintain a data governance framework that aligns with the University (as defined by the UDO) and Advancement's objectives and data strategy. Platform Security Work with CISO office to establish roadmap for application, information and data security tools and policies as they relate to Advancement. Ensure alignment with OIT and CISO strategic planning Oversee deployment and communication of new tools and policies to ensure that Advancement systems and data are secured to the greatest extent possible Maintain and update security roles aligned with University business needs and University policy Serve as a liaison between business and functional areas and technology to ensure that business requirements for protecting sensitive data are clearly defined and communicated Facilitate the development and implementation of data protection standards and adoption requirements for all designated users of alumni and donor data Data Management Set, communicate, and provide direction on data integrity protocols, data hygiene standards, and data management strategies Collaborate with Data Strategy & Innovation colleagues to ensure that alumni and donor data is used in a manner that is consistent with laws and regulations, as well as University policies on data security and privacy Establish, communicate and manage record retention policy in alignment with Advancement and University policies Work closely with Advancement's data management and reporting teams to support the foundation for data-driven decision-making Partner with Data Strategy & Innovation leadership to identify, develop, and execute large scale advancement data management initiatives Maintain systems to monitor quality control and oversight of data collection and entry in order to adequately meet the data management needs of Advancement Participate in cross-functional teams and projects, ensuring thorough documentation of processes and knowledge sharing, while maintaining clear and consistent communication Continually assess and improve the data management program to adapt to changing needs, technologies, and regulatory environments Special Projects Undertakes special projects and other duties as assigned. Qualifications Education: Bachelor's degree required 8+ years of relevant practical experience Proficiency with technology and systems Ability to quickly learn new systems and processes Excellent written and oral communication skills Discretion in dealing with highly confidential material Excellent interpersonal skills and a high degree of professionalism and initiative Excellent attention to detail; accuracy, flexibility and demonstrated ability to be proactive and to prioritize tasks Strong problem-solving, data gathering and organizational skills Strong computer skills, including proficiency in the Microsoft Office suite of applications (Word, Excel, PowerPoint and Outlook), CRM databases, ability to learn and manage alumni database information Customer service orientation Demonstrated ability to exercise independent judgment and make decisions based on established policies and procedures, and ability to interact with department staff, University Advancement staff and campus partners Commitment to University Advancement's mission to inform, involve, and inspire Princeton's global community of alumni and friends, and adhering to its guiding principles of High Performance, Innovation, Civility, and Collaboration. Preferred Knowledge of Princeton's mission Experience in higher education Prior experience in an educational or fundraising setting a plus Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly. If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information. PI0a6476f85cbf-7631

Overview As part of University Advancement Data Strategy and Innovation team, the role of the Associate Director, Data Science is to turn data into tactical information and knowledge by applying statistical, algorithmic, mining and visualization techniques. Data Strategy and Innovation plays a critical strategic role within Advancement, providing the analytical framework, data architecture, application development, and tools for data-driven decision making at all levels of the organization. The person in this role should be a creative thinker and propose innovative ways to look at problems that can be used to make sound organizational decisions. The Associate Director, Data Science will need to be able to present their findings and communicate data in ways that can be easily understood by their business counterparts. Working with the department Executive Director, this role will supervise the activities of the data science team and provide management of day to day functional operations. This position is a hands-on role, requiring active involvement in day-to-day technical operations, problem-solving, and project execution in addition to management responsibilities.In addition, this position will serve as a liaison to other teams within University Advancement - acting as a lead and driving strategic planning to successfully execute analytics strategies and solutions in support of the University fundraising and engagement operations. Responsibilities Statistical Modeling and Technical Exploration Utilizing a combination of business focus, strong analytical and problem-solving skills and programming knowledge, drive new innovations and data exploration Develop recommendation engines or automated lead scoring systems to drive our prospect management strategy and marketing segmentation, utilizing machine learning techniques Work with structured data and drive innovation in unstructured data architecture and analysis Work with statistical programming language, like R or Python, and database querying language like PL/SQL Utilize innovative approaches to drive knowledge, incorporate and promote a big data environment. Identify what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as social media and web analytics Communication, Mentoring and Analytics Implementation Work with business users to define desired outcomes and business requirements of analyses, data visualization and other reporting Provide expertise on mathematical concepts for broader applied analytics and inspire the adoption of advanced analytics and data science across the Advancement Office Describe findings or the way techniques work to audiences, both technical and non-technical, effectively using presentation tools such as data visualization, PowerPoint and documentation to drive strategic decision making and understanding of business analytics at all levels of the organization Assist in addressing daily operational questions as needed, identify critical process improvement areas and collaborate in developing procedures and solutions for enhancing a high level of customer service Staff Management Serve as the team lead for projects and priorities of the data science team, working closely with the Executive Director, Prospect, Engagement, and Data Strategy to ensure projects are aligned with department and Advancement priorities Responsible for the hiring and professional development of staff including training, mentoring, and identifying goals, objectives and metrics Responsible for performance management of staff and monitoring of activity and metrics Other related tasks as assigned Best Practices & Strategy Working closely with Data Strategy and Innovation team members, conceive of and contribute to strategies and best practices in maintaining a comprehensive, reliable, and innovative data environment Review and recommend use of new technologies, vendor services and information sources. Keep abreast of news and relevant industry trends in support of the Office of Advancement Develop and maintain proficiency in using advanced analytic and database tools, internet resources, in-house data, and other references Qualifications 7+ years of professional experience required in an analytical or information specialist role within an academic, nonprofit, corporate or consulting setting. Deep understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques, and recommendation and optimization algorithms. Keen desire to solve business problems, and to find patterns and insights within structured and unstructured data. Expert in analyzing large, complex, multi-dimensional datasets with a variety of tools. Accomplished in the use of statistical analysis environments such as R, MATLAB, SPSS or SAS. Experience with BI tools such as Tableau. Having a good understanding of relational databases, warehouse design and architecture principles. Familiarity with big data frameworks (e.g., such as Hadoop, Hive, Spark). Good scripting and programming skills (e.g. familiarity with SQL, Python, Java). Strong foundation in statistical, mathematical, predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find effective answers. Familiar with disciplines such as: natural language processing, machine learning, conceptual modelling, statistical analysis, predictive modeling and hypothesis testing. Able to create examples, prototypes, demonstrations to help management better understand the work. Able to work autonomously. Proficiency at planning and setting meaningful objectives to meet office goals. Ability to articulate and promote goals and implement strategic plans. Education: Bachelor's Degree in operations research, applied statistics, data mining, machine learning, or a related quantitative discipline required. Preferred: Knowledge of Princeton's mission Experience in higher education Master's degree or Ph.D. strongly preferred Understanding of philanthropy (mission, practice, trends) and fundraising practices (the development cycle, prospect management policies and practices) preferred. Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly. If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information. PI4bd262fb5-

Overview The Lead Systems Engineer for High Performance Computing (HPC) and Artificial Intelligence (AI) works as part of the Advanced Systems team within Research Computing that supports the hardware and system-level software on the University's centralized high-performance computing and other computing for research systems. The Lead Systems Engineer is responsible for engaging with faculty, researchers, vendors, and other information technology (IT) staff to specify, design, install, and administer computing for research systems while also providing insight into trends and technologies supporting the advancement of AI research. The Lead Systems Engineer is also expected to be in tune to trends in computational research and will be asked to evaluate, pilot, and implement systems that advance Princeton's HPC and AI technologies enhancing Research Computing services. The Lead Systems Engineer serves as an expert for HPC and AI hardware and software and helps researchers troubleshoot system level problems with software, data, and job submission. This position requires one to work closely with colleagues at all levels of technical understanding in the Office of Information Technology (OIT) and University academic departments to provide timely and creative support for research computing. The Lead Systems Engineer is required to work well on teams and independently, and will be asked to lead initiatives within Advanced Systems, requiring only general supervision. On-call rotation is a mandatory facet of this role, requiring infrequent off-hour and weekend duty. Responsibilities Operations: Design, maintain, troubleshoot, and refine advanced HPC/AI cluster infrastructure including high performance interconnects, cluster schedulers, and configuration management across research systems. Partner with colleagues in Advanced Data and Storage Management to align designs for scratch filesystems and data management with cluster designs. Develop data-transfer pathways and networks to support AI driven computing workloads. Establish and maintain best practices for cluster management and usage to support AI-driven workloads. Develop documentation for users and technical staff that can be used by the larger community. Develop, enhance, and expand monitoring infrastructure and related protocols for research computing systems. Plan and implement scheduled maintenance of operations, including during off hours. Perform other tasks as assigned. Technical Leadership: Define and drive the institutional technical strategy for advanced AI and data intensive HPC. Bring creativity, foresight, and mature professional judgment in anticipating and solving novel and complex problems, in determining project objectives and requirements, and in developing standards and governance for all research computing platforms. Leveraging expertise in AI technologies, identify, evaluate, and pilot researcher-facing systems that enable the acceleration of research using AI. Lead the implementation and expand adoption of modern, automation-driven infrastructure and cluster management practices. Promote institution wide collaboration as the community expert advising and working with faculty, researchers and vendors on emerging trends and challenges in AI enabled research computing. Cultivate a collaborative, knowledge sharing environment by providing technical mentorship to systems specialists and analysts by sharing designs and operational expertise across data systems and HPC/AI infrastructure. Contribute to the strategic vision for HPC/AI systems; Advise senior leadership and stakeholders on strategic investments, risks, and opportunities related to research infrastructure. Troubleshooting and Problem Resolution: Monitor HPC clusters, networks, and storage systems for abnormalities, and resolve issues. Analyze and solve problems in Linux and HPC/AI computing environments with software, data, and job submissions. Use scripting and programming tools to troubleshoot issues. Qualifications Essential Qualifications: 10+ years of strong experience managing advanced research computing systems. Strong expertise with Linux system administration, installation, and troubleshooting. Advanced experience writing scripts in languages such as bash, Python and/or Perl. Proficient in managing networking in HPC environments. Strong experience managing software in an advanced research computing environment. Experience supporting scheduling and managing jobs (SLURM) in large-scale computing environments. Strong oral and written communication skills, with the ability to proactively engage peers and communicate effectively across a diverse stakeholder community. Strong ability to solve complex and system infrastructure problems, and share expertise with colleagues at all levels. Demonstrated ability to collaborate across teams to solve systems and infrastructure challenges, aligning day to day operational needs with longer term technical and organizational goals as technologies evolve. When provided access to personal, proprietary and/or otherwise confidential data, maintain such data in the strictest confidence and follow procedures to ensure the privacy, security, and proper use of data. Education: Bachelors degree in a related field or equivalent experience. Preferred Qualifications: Experience working in an academic and research settings. Experience supporting AI driven research in open and secure computing environments. Familiarity using and administering data-transfer technologies such as Globus that facilitate the transfer of large datasets. Experience using and supporting parallel file systems that are commonly used in HPC/AI systems. Experience supporting unstructured data in HPC/AI environments. Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly. If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information. PIc3ef4d97aa50-8951