... Banner (direct or through Cognos), Slate, Common Application (Common App), and Workday, as well as ... and security for trusted reporting. 10. Design, deploy, and automate interactive dashboards ...
... Banner (direct or through Cognos), Slate, Common Application (Common App), and Workday, as well as ... and security for trusted reporting. 10. Design, deploy, and automate interactive dashboards ...
Academic Advisor
Guttenberg, IA · On-site
$64K - $103K/yr
Director of Administration Position Summary: Reporting to the Director of Academic Advisement in ... Working knowledge of Banner information systems or Workday systems is also preferred. At the ...
Academic Advisor
Guttenberg, IA · On-site
$64K - $103K/yr
Director of Administration Position Summary: Reporting to the Director of Academic Advisement in ... Working knowledge of Banner information systems or Workday systems is also preferred. At the ...
Director Banner Security information
What does a director banner security do?
A Director of Banner Security is responsible for overseeing and managing all aspects of security related to the Banner system, which is an enterprise resource planning (ERP) software commonly used in educational institutions. This role involves developing security policies, ensuring compliance with regulatory standards, monitoring for security threats, and coordinating responses to incidents. The director also leads a team to manage user access, protect sensitive data, and implement best practices for system integrity. Collaboration with IT and administrative departments is essential to maintain a secure and efficient environment.
How does a director banner security typically collaborate with other departments to ensure comprehensive organizational protection?
A Director of Banner Security works closely with IT, compliance, legal, and operations teams to create and enforce security policies and procedures. This role often involves leading cross-functional risk assessments, coordinating incident response plans, and ensuring that security initiatives align with organizational goals. Regular meetings and updates with department heads are common to address emerging threats, share best practices, and foster a culture of security awareness throughout the company. Effective collaboration helps to ensure that security protocols are integrated seamlessly into daily operations, minimizing vulnerabilities.
What are the key skills and qualifications needed to thrive as a director banner security, and why are they important?
To thrive as a Director of Banner Security, you need extensive experience in information security management, risk assessment, and a relevant bachelor's or master's degree, often supported by certifications such as CISSP or CISM. Familiarity with security information and event management (SIEM) systems, intrusion detection tools, and compliance frameworks like HIPAA or PCI-DSS is crucial. Strong leadership, crisis management, and communication skills help in guiding teams and collaborating across departments. These competencies ensure robust protection of organizational data, regulatory compliance, and effective response to evolving security threats.
What is the difference between Director Banner Security vs Security Manager?
| Aspect | Director Banner Security | Security Manager |
|---|---|---|
| Credentials | Security certifications, leadership experience | Security certifications, operational experience |
| Work Environment | Strategic planning, overseeing security policies | Managing security teams, daily operations |
| Employer & Industry | Educational institutions, large organizations | Corporate, government, or private sectors |
| Search & Comparison Intent | Understanding leadership roles in security | Operational security management |
The main difference between Director Banner Security and Security Manager lies in their scope and focus. The Director Banner Security typically handles strategic planning and policy oversight at a higher level, while the Security Manager focuses on daily operations and team management. Both roles require security certifications and experience, but the Director role emphasizes leadership and long-term security strategies.
What are popular job titles related to Director Banner Security jobs in Iowa?
For Director Banner Security jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Director Banner Security jobs in Iowa look for?
The top searched job categories for Director Banner Security jobs in Iowa are:
What cities in Iowa are hiring for Director Banner Security jobs?
Cities in Iowa with the most Director Banner Security job openings:
Full-time
Re-posted 14 days ago
Key responsibilities
Apply advanced statistical modeling, machine learning, and predictive analytics methods to institutional data to support university-wide analytical initiatives and operational efficiency.
Design, implement, and operationalize automated end-to-end statistical and machine learning workflows using Python, R, and DataRobot, integrating Snowflake and custom applications for model training, scoring, validation, monitoring, and deployment.
Develop and deploy AI agent-based decision-support systems that enable faculty and administrators to query, explore, and interpret institutional data using natural language and large language models.
Job description
Title:
Senior Data Scientist & AI Engineer
Department:
Director, Data Analytics
Reports To:
Director, Learning Technologies
Position Summary:
1. Apply advanced statistical modeling, machine learning, and predictive analytics methods including time-series forecasting (ARIMA, Prophet, LSTM), survival analysis
(Kaplan-Meier, Cox regression), and optimization techniques to institutional data requiring domain knowledge of admissions, financial aid, enrollment, and student
success data to support university-wide analytical initiatives and operational efficiency. 2. Design, implement, and operationalize automated end-to-end statistical and machine
learning workflows using Python, R, and DataRobot, integrating Snowflake via DataRobot REST APIs and custom Streamlit applications to automate model training,
scoring, validation, monitoring, and controlled production deployment.
3. Architect, build, and deploy production-grade AI agent-based decision-support systems (including model configuration and fine-tuning) that enable faculty and administrators to
query, explore, and interpret governed institutional data using natural language, by developing large language model (LLM)-powered agents and retrieval-augmented generation (RAG) pipelines integrated with Snowflake and enterprise data sources to support university-wide analytics.
4. Integrate, manage and process data from multiple higher-education-related data systems, including Banner (direct or through Cognos), Slate, Common Application (Common App), and Workday, as well as external higher-education datasets including IPEDS and National Student Clearinghouse.
5. Identify, define, and validate analytical attributes, measures, dimensions, and derived metrics within enterprise and external higher-education datasets by designing and maintaining analytically meaningful data models and semantic layers (e.g., fact and dimension structures) that translate raw institutional data into consistent, reporting-ready structures supporting statistical analysis, machine learning, AI development, and institutional planning.
6. Respond to data requests by writing and optimizing complex SQL queries and Snowpark python scripts to extract, join, aggregate, and validate large-scale institutional datasets stored in the Snowflake Data Warehouse, including development of custom, reusable analytical views integrating cross-departmental data.
7. Oversee and perform data extraction, transformation, feature engineering, and validation using SQL, Python, R, and Snowpark to build and maintain scalable data pipelines that prepare structured and unstructured data for modeling and AI applications.
8. Collaborate with Data Governance stakeholders to define analytical requirements and support accurate, governed institutional data; contribute to documentation and validation
of business and technical data definitions using Data Cookbook, ensuring consistency, reproducibility, and compliance within institutional analytics.
9. Certify dashboards and metrics through reviews of the underlying data, mathematical assumptions, transformations, and calculations applied; formally approve dashboards
and ensure appropriate access controls and security for trusted reporting.
10. Design, deploy, and automate interactive dashboards, analytical workflows, and self-service analytics products using Strategy (MicroStrategy) and Snowflake Warehouse
through an iterative development process of gathering stakeholder requirements and incorporating feedback to operationalize institutional metrics and AI-generated insights, and communicate complex analytical findings to support actionable decision-making.
11. Establish and maintain version control and model governance best practices using Git and related tools to manage SQL code, analytical scripts, AI models, dashboards, and
documentation across development and production environments; coordinate analytics and data project workflows using ServiceNow utilizing Agile/SCRUM methodologies to
ensure reproducibility, collaboration, and controlled deployment.
12. Mentor graduate students and junior data scientists, leading technical ideation for strategic projects involving mathematical modeling, machine learning model development, and design of statistical hypothesis tests (e.g., regression-based inference and experimental evaluation), and providing guidance in Python- and SQL-based data analysis, AI engineering, and development of AI-enabled applications.
EDUCATION AND EXPERIENCE REQUIREMENT:
Requires a Ph.D. in Mathematics or Related Field and 1 year of experience in job offered or 1 year of experience in the Related Occupation.
RELATED OCCUPATION:
Data Scientist or any other job title performing the following job duties:
1. Applied advanced statistical modeling, machine learning, and predictive analytics methods including time-series forecasting (ARIMA, Prophet, LSTM), survival analysis (Kaplan-Meier, Cox regression), and optimization techniques to institutional data requiring domain knowledge of admissions, financial aid, enrollment, and student success data to support university-wide analytical initiatives and operational efficiency.
2. Designed, implemented, and operationalized automated end-to-end statistical and machine learning workflows using Python, R, and DataRobot, integrating Snowflake via DataRobot REST APIs and custom Streamlit applications to automate model training, scoring, validation, monitoring, and controlled production deployment.
3. Integrated, managed and processed data from multiple higher-education-related data systems, including Banner (direct or through Cognos), Slate, Common Application (Common App), and Workday, as well as external higher-education datasets including IPEDS and National Student Clearinghouse.
4. Responded to data requests by writing and optimizing complex SQL queries and Snowpark python scripts to extract, join, aggregate, and validate large-scale institutional datasets stored in the Snowflake Data Warehouse, including development of custom, reusable analytical views integrating cross-departmental data.
5. Collaborated with Data Governance stakeholders to define analytical requirements and supported accurate, governed institutional data; contributed to documentation and validation of business and technical data definitions using Data Cookbook, ensured consistency, reproducibility, and compliance within institutional analytics.
6. Assisted the Lead Data Scientist with exploratory artificial intelligence and natural language processing initiatives in higher-education contexts by writing Python- and SQL-based code to test and evaluate large language models (including models accessed through Snowflake Cortex); conducted prompt experiments, reviewed and validated generated outputs against institutional data and use cases, and summarized experimental results to inform future projects as determined by the Lead Data Scientist.
7. Examined student, academic, and operational data using statistical summaries and visualizations to support subsequent modeling, reporting, and analytical inquiries aligned
with strategic institutional priorities; assisted senior team members in designing and creating custom analytical views and data structures.
8. In support of feature engineering and data processing efforts, wrote SQL queries and Python-, R-, and Snowpark-based scripts to extract, clean, and transform data; assisted the Lead Data Scientist by preparing analysis-ready datasets, validating transformations, and troubleshooting data issues during experimentation.
9. Reviewed analytical outputs, dashboards and metrics for accuracy and consistency by verifying calculations, assumptions, and data transformations; assisted senior team members by identifying discrepancies, testing dashboard functionality, and documenting data definitions used in reports and analyses.
10. Built dashboards, reports, tables, and visualizations in MicroStrategy and Snowflake based on requirements, wireframes, and specifications provided by the Director of Data Analytics; prepared analytical outputs to support academic and administrative reporting purposes.
11. Maintained analytical code, SQL queries, and documentation following departmental best practices; followed team standards for organizing scripts, documenting assumptions, and supporting reproducibility of analyses across projects; used ServiceNow to track assigned tasks and follow team workflows.
12. Provided technical guidance and support to student employees on projects developed by the Lead Data Scientist, including mathematical modeling and machine learning projects involving Python- and SQL-based data analysis and model experimentation tasks.
SALARY RANGE:
$90,272.00 to $121,800.00/year
At the university's discretion, the education and experience prerequisites may be exempted where the candidate can demonstrate to the satisfaction of the university an equivalent combination of education and experience specifically preparing the candidate for success in the position.
Union:
Professional Staff Association (PSA)
Range:
Professional Staff -28
Compensation:
$79,241.00 - $148,916.00
NJIT considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer. This pay range represents base pay only and excludes any additional items such as incentives, bonuses, or other items.
FLSA:
Exempt
Time Type:
Full time
Pay Rate:
Salary
Additional Information:
As an EEO employer NJIT is committed to building a diverse and inclusive teaching, research, and working environment and strongly encourages applications from individuals with disabilities, minorities, veterans, and women.
Employment at NJIT is subject to the provisions of New Jersey First Act which mandates new employees, who are not NJ residents, to establish primary residence in New Jersey within one year of their appointment to certain positions. The law does not apply to any individual employed at NJIT on a temporary or per semester basis as a visiting or adjunct professor, teacher, lecturer, researcher or administrator. For more information on the act please click here.
If special accommodations are needed in applying for a position, please visit the Department of Human Resources located in Fenster Hall, 5th Floor, University Heights, Newark, NJ 07102 or call (973) 596-3140. If you have questions, please email the Human Resources Department at hr@njit.edu.
Information regarding NJIT campus security, personal safety, and fire safety including topics such as, disciplinary procedures, crime prevention, NJIT Police law enforcement authority, crime reporting policies, and crime statistics for the most recent three year period is available on the NJIT Department of Public Safety here.
NJIT is an E-Verify employer and uses E-Verify to confirm work authorization of each new hire.
Senior Data Scientist & AI Engineer
Department:
Director, Data Analytics
Reports To:
Director, Learning Technologies
Position Summary:
1. Apply advanced statistical modeling, machine learning, and predictive analytics methods including time-series forecasting (ARIMA, Prophet, LSTM), survival analysis
(Kaplan-Meier, Cox regression), and optimization techniques to institutional data requiring domain knowledge of admissions, financial aid, enrollment, and student
success data to support university-wide analytical initiatives and operational efficiency. 2. Design, implement, and operationalize automated end-to-end statistical and machine
learning workflows using Python, R, and DataRobot, integrating Snowflake via DataRobot REST APIs and custom Streamlit applications to automate model training,
scoring, validation, monitoring, and controlled production deployment.
3. Architect, build, and deploy production-grade AI agent-based decision-support systems (including model configuration and fine-tuning) that enable faculty and administrators to
query, explore, and interpret governed institutional data using natural language, by developing large language model (LLM)-powered agents and retrieval-augmented generation (RAG) pipelines integrated with Snowflake and enterprise data sources to support university-wide analytics.
4. Integrate, manage and process data from multiple higher-education-related data systems, including Banner (direct or through Cognos), Slate, Common Application (Common App), and Workday, as well as external higher-education datasets including IPEDS and National Student Clearinghouse.
5. Identify, define, and validate analytical attributes, measures, dimensions, and derived metrics within enterprise and external higher-education datasets by designing and maintaining analytically meaningful data models and semantic layers (e.g., fact and dimension structures) that translate raw institutional data into consistent, reporting-ready structures supporting statistical analysis, machine learning, AI development, and institutional planning.
6. Respond to data requests by writing and optimizing complex SQL queries and Snowpark python scripts to extract, join, aggregate, and validate large-scale institutional datasets stored in the Snowflake Data Warehouse, including development of custom, reusable analytical views integrating cross-departmental data.
7. Oversee and perform data extraction, transformation, feature engineering, and validation using SQL, Python, R, and Snowpark to build and maintain scalable data pipelines that prepare structured and unstructured data for modeling and AI applications.
8. Collaborate with Data Governance stakeholders to define analytical requirements and support accurate, governed institutional data; contribute to documentation and validation
of business and technical data definitions using Data Cookbook, ensuring consistency, reproducibility, and compliance within institutional analytics.
9. Certify dashboards and metrics through reviews of the underlying data, mathematical assumptions, transformations, and calculations applied; formally approve dashboards
and ensure appropriate access controls and security for trusted reporting.
10. Design, deploy, and automate interactive dashboards, analytical workflows, and self-service analytics products using Strategy (MicroStrategy) and Snowflake Warehouse
through an iterative development process of gathering stakeholder requirements and incorporating feedback to operationalize institutional metrics and AI-generated insights, and communicate complex analytical findings to support actionable decision-making.
11. Establish and maintain version control and model governance best practices using Git and related tools to manage SQL code, analytical scripts, AI models, dashboards, and
documentation across development and production environments; coordinate analytics and data project workflows using ServiceNow utilizing Agile/SCRUM methodologies to
ensure reproducibility, collaboration, and controlled deployment.
12. Mentor graduate students and junior data scientists, leading technical ideation for strategic projects involving mathematical modeling, machine learning model development, and design of statistical hypothesis tests (e.g., regression-based inference and experimental evaluation), and providing guidance in Python- and SQL-based data analysis, AI engineering, and development of AI-enabled applications.
EDUCATION AND EXPERIENCE REQUIREMENT:
Requires a Ph.D. in Mathematics or Related Field and 1 year of experience in job offered or 1 year of experience in the Related Occupation.
RELATED OCCUPATION:
Data Scientist or any other job title performing the following job duties:
1. Applied advanced statistical modeling, machine learning, and predictive analytics methods including time-series forecasting (ARIMA, Prophet, LSTM), survival analysis (Kaplan-Meier, Cox regression), and optimization techniques to institutional data requiring domain knowledge of admissions, financial aid, enrollment, and student success data to support university-wide analytical initiatives and operational efficiency.
2. Designed, implemented, and operationalized automated end-to-end statistical and machine learning workflows using Python, R, and DataRobot, integrating Snowflake via DataRobot REST APIs and custom Streamlit applications to automate model training, scoring, validation, monitoring, and controlled production deployment.
3. Integrated, managed and processed data from multiple higher-education-related data systems, including Banner (direct or through Cognos), Slate, Common Application (Common App), and Workday, as well as external higher-education datasets including IPEDS and National Student Clearinghouse.
4. Responded to data requests by writing and optimizing complex SQL queries and Snowpark python scripts to extract, join, aggregate, and validate large-scale institutional datasets stored in the Snowflake Data Warehouse, including development of custom, reusable analytical views integrating cross-departmental data.
5. Collaborated with Data Governance stakeholders to define analytical requirements and supported accurate, governed institutional data; contributed to documentation and validation of business and technical data definitions using Data Cookbook, ensured consistency, reproducibility, and compliance within institutional analytics.
6. Assisted the Lead Data Scientist with exploratory artificial intelligence and natural language processing initiatives in higher-education contexts by writing Python- and SQL-based code to test and evaluate large language models (including models accessed through Snowflake Cortex); conducted prompt experiments, reviewed and validated generated outputs against institutional data and use cases, and summarized experimental results to inform future projects as determined by the Lead Data Scientist.
7. Examined student, academic, and operational data using statistical summaries and visualizations to support subsequent modeling, reporting, and analytical inquiries aligned
with strategic institutional priorities; assisted senior team members in designing and creating custom analytical views and data structures.
8. In support of feature engineering and data processing efforts, wrote SQL queries and Python-, R-, and Snowpark-based scripts to extract, clean, and transform data; assisted the Lead Data Scientist by preparing analysis-ready datasets, validating transformations, and troubleshooting data issues during experimentation.
9. Reviewed analytical outputs, dashboards and metrics for accuracy and consistency by verifying calculations, assumptions, and data transformations; assisted senior team members by identifying discrepancies, testing dashboard functionality, and documenting data definitions used in reports and analyses.
10. Built dashboards, reports, tables, and visualizations in MicroStrategy and Snowflake based on requirements, wireframes, and specifications provided by the Director of Data Analytics; prepared analytical outputs to support academic and administrative reporting purposes.
11. Maintained analytical code, SQL queries, and documentation following departmental best practices; followed team standards for organizing scripts, documenting assumptions, and supporting reproducibility of analyses across projects; used ServiceNow to track assigned tasks and follow team workflows.
12. Provided technical guidance and support to student employees on projects developed by the Lead Data Scientist, including mathematical modeling and machine learning projects involving Python- and SQL-based data analysis and model experimentation tasks.
SALARY RANGE:
$90,272.00 to $121,800.00/year
At the university's discretion, the education and experience prerequisites may be exempted where the candidate can demonstrate to the satisfaction of the university an equivalent combination of education and experience specifically preparing the candidate for success in the position.
Union:
Professional Staff Association (PSA)
Range:
Professional Staff -28
Compensation:
$79,241.00 - $148,916.00
NJIT considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer. This pay range represents base pay only and excludes any additional items such as incentives, bonuses, or other items.
FLSA:
Exempt
Time Type:
Full time
Pay Rate:
Salary
Additional Information:
As an EEO employer NJIT is committed to building a diverse and inclusive teaching, research, and working environment and strongly encourages applications from individuals with disabilities, minorities, veterans, and women.
Employment at NJIT is subject to the provisions of New Jersey First Act which mandates new employees, who are not NJ residents, to establish primary residence in New Jersey within one year of their appointment to certain positions. The law does not apply to any individual employed at NJIT on a temporary or per semester basis as a visiting or adjunct professor, teacher, lecturer, researcher or administrator. For more information on the act please click here.
If special accommodations are needed in applying for a position, please visit the Department of Human Resources located in Fenster Hall, 5th Floor, University Heights, Newark, NJ 07102 or call (973) 596-3140. If you have questions, please email the Human Resources Department at hr@njit.edu.
Information regarding NJIT campus security, personal safety, and fire safety including topics such as, disciplinary procedures, crime prevention, NJIT Police law enforcement authority, crime reporting policies, and crime statistics for the most recent three year period is available on the NJIT Department of Public Safety here.
NJIT is an E-Verify employer and uses E-Verify to confirm work authorization of each new hire.
About New Jersey Institute of Technology
Sourced by ZipRecruiter
Industry
Colleges, universities, and professional schools
Company size
1,001 - 5,000 Employees
Headquarters location
Newark, NJ, US
Year founded
1881