Bridging Specialist (Systems & Data), Academic Success Center

Responsibilities (tasks, key areas of responsibility, and functions):

Data Analysis and Academic Risk Identification: Performs data analysis of student academic activity within institutional data systems to identify risk patterns and support early intervention for improved student outcomes.

Functions:

1. Collects and analyzes data from Learning Management Systems (LMS) and Student Information Systems (SIS);
2. Identifies academic risk patterns, behavioral indicators, and predictive failure points;
3. Develops and applies analytical models to detect early warning signals (e.g., disengagement, absence patterns);
4. Provides data-driven insights to ASC teams to support decision-making.

Systems Integration and Data Infrastructure Management: Ensures integration and stable operation of academic data systems within the University’s digital architecture to support seamless data exchange and operational efficiency.

Functions:

1. Manages integration between LMS, SIS, and other relevant systems;
2. Maintains API connections, data synchronization, and system interoperability;
3. Monitors system performance and resolves data inconsistencies or integration issues;
4. Ensures reliability and continuity of data flows supporting ASC operations.

Retention Analytics and Intervention Support: Supports implementation of student retention initiatives through data-driven intervention mechanisms within institutional frameworks to improve retention and engagement.

Functions:

1. Supports execution of RISE early intervention protocols;
2. Monitors and triggers intervention workflows based on identified risk indicators;
3. Supports automation of communication tools (e.g., alerts, notifications);
4. Tracks effectiveness of intervention actions and proposes improvements.

Assessment, Reporting, and Data Visualization: Ensures measurement and reporting of ASC program effectiveness using analytical tools within institutional reporting frameworks to support performance evaluation and improvement.

Functions:

1. Conducts surveys and collects feedback from students and faculty;
2. Analyzes program effectiveness, including impact and return on investment (ROI);
3. Develops dashboards, reports, and data visualizations for stakeholders;
4. Prepares analytical reports and recommendations for ASC leadership.

Data Governance and Quality Assurance: Ensures data accuracy, integrity, and compliance with internal and regulatory requirements within institutional data governance frameworks.

Functions:

1. Ensures accuracy, consistency, and completeness of data used in analysis;
2. Maintains proper data documentation and data management practices;
3. Ensures compliance with data protection, confidentiality, and internal policies;
4. Supports implementation of data governance standards within ASC processes.

Cross-Functional Data Support: Provides analytical support to ASC units and stakeholders within institutional frameworks to enhance coordination and effectiveness of student success initiatives.

Functions:

1. Collaborates with ASC teams (Advising, Tutoring, Curriculum) to support data needs;
2. Provides analytical input for program design and improvement;
3. Supports integration of data insights into operational decision-making;
4. Facilitates use of data tools and dashboards by stakeholders.

Education requirements (level, field, licenses, professional certifications, etc.):

        -      Master's degree in Data Science, Computer Science, Information Systems, Statistics, or a related field (highly preferred)

Work experience requirements:

1. Minimum of 4 years of professional experience in data analytics, CRM management, or systems engineering;
2. Experience ideally within a higher education or enterprise-level environment

Knowledge, skills, and competencies requirements:

1. Technical fluency in Python and SQL for data manipulation and mathematical modeling
2. Advanced proficiency in LMS/SIS integration (e.g., Moodle, Serosoft/Academia) and CRM management
3. Strong understanding of the education legislation of the Republic of Kazakhstan

Language requirements:

- Fluency in English, Kazakh, and Russian

Recruitment and selection process
Recruitment and selection at Nazarbayev University include the following process: preliminary selection based on experience and qualifications, assessments (e.g. technical skills/capabilities, aptitude, personality, work samples, in-basket exercises, and informal interviews), and motivation.
Formal interviews form the final stage of the selection process.
They are typically based on organizational values and behaviors and conducted in English.
You are encouraged to share your views and values  to identify how they fit into  Nazarbayev University core values

Recruitment and selection process
Recruitment and selection at Nazarbayev University include the following process: preliminary selection based on experience and qualifications, assessments (e.g. technical skills/capabilities, aptitude, personality, work samples, in-basket exercises, and informal interviews), and motivation.
Formal interviews form the final stage of the selection process.
They are typically based on organizational values and behaviors and conducted in English.
You are encouraged to share your views and values  to identify how they fit into  Nazarbayev University core values