Lead, Data Analytics

• Company Asia Pacific University of Technology & Innovation
• No. of Openings 10+
• Salary Not Disclosed
• Work Type on-site

Job Description :

A Lead Data Analytics, position is responsible to assist the academic operations team by analyzing, interpreting, and reporting data using different approaches and business intelligence tools, which would assist the team and the leadership in uncovering key insights that lead to better informed and successful decision-making. The role will involve using knowledge and skills to turn raw data into meaningful statistics, information and insight.

1. Apply data analytics, for data driven and timely decision by the leadership team across the university, with direct reporting to Director, Academic Operations.  
2. Work closely with CTI in the data collection systems, data analytics and other strategies that optimize statistical efficiency and quality
3. Analyse and provide statistics on student satisfaction, experience based on student surveys – mid/end semester, programme evaluation survey as well as ad-hoc online feedback - and assist leadership in the analysis of the findings for informed and effective decision making.
4. Provide in-depth information on the rate of student attrition over a period of time, with insights on the programmes, number of students as well reasons for attrition.
5. Contribute towards teaching/learning, by undertaking module delivery as well as module content creation of a few select modules in which he/she has the expertise.
6. Take on any other administrative role that contributes towards effective academic operations across the university, assigned by the Director, Academic Operations.

Job requirement

1. Minimum Degree in Analytics /Data Science / Statistics / Computer Science or any related field.
2. Working experience of at least 5 years in related Big Data Analytic fields.
3. Statistical mind set; exceptional analytical and problem-solving skills
4. Ability to rapidly connect and match analytics and data products to business needs.
5. Technical proficiency regarding database design development, data models, techniques for data mining, and segmentation.
6. Demonstrated ability to articulate challenges in high-stakes decision making that is supported by information semantics and AI.
7. Proficiency in statistics and statistical packages like Excel, SPSS, SAS to be used for data set analyzing
8. Experience with statistical software
9. Reporting and data visualization skills