Sign up with

Already have an account? Log in here

Need some help?
Talk to us at +91 7670800001

Data and AI Automation Specialist at LinkedIn

Dubai, Dubai, United Arab Emirates -

Full Time

Start Date

Immediate

Expiry Date

22 Dec, 26

Salary

25000.0

Posted On

23 Sep, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Industry

Information Technology & Services

Description

Key Responsibilities:Academic and divisional data analysis Collect, integrate, clean, validate, and analyze quantitative and qualitative data relevant to CMS programs, courses, students, faculty, research, and operations.
Analyze curriculum delivery, course demand, teaching activity, student outcomes, faculty workload, research productivity, and resource utilization to provide evidence for curriculum planning, course scheduling, student success initiatives, faculty and resource planning, program review, and continuous improvement.
Apply appropriate statistical methods, trend analysis, forecasting, segmentation, and predictive techniques to identify patterns, risks, and opportunities within CMS.
Investigate data anomalies, reconcile conflicting sources with relevant data owners and Institutional Research, and document assumptions and limitations before results are released.

How To Apply:

Incase you would like to apply to this job directly from the source, please click here

Responsibilities

Key Responsibilities:Academic and divisional data analysis Collect, integrate, clean, validate, and analyze quantitative and qualitative data relevant to CMS programs, courses, students, faculty, research, and operations.
Analyze curriculum delivery, course demand, teaching activity, student outcomes, faculty workload, research productivity, and resource utilization to provide evidence for curriculum planning, course scheduling, student success initiatives, faculty and resource planning, program review, and continuous improvement.
Apply appropriate statistical methods, trend analysis, forecasting, segmentation, and predictive techniques to identify patterns, risks, and opportunities within CMS.
Investigate data anomalies, reconcile conflicting sources with relevant data owners and Institutional Research, and document assumptions and limitations before results are released.