[What you will be working on]

You will perform the following tasks in order to support our full time and part-time course offerings in areas related to Data Analytics with Machine Learning, Data Engineering and Data Management and other foundational ICT modules.

• Facilitate, implement and administer module delivery, related activities (including student assessments and assignments) to meet learning outcomes, in assigned subject areas, according to RP's pedagogical practices.
• Planning, designing and developing module curriculum, learning activities and materials (including ICT-enabled learning) that are applied, aligned with course learning outcomes and responsive to the needs of the industry
• Create opportunities in the module and/or student activities to facilitate the holistic development of students
• Implement a range of appropriate teaching & learning strategies to facilitate effective active learning.
• Implement a range of interventions to address the diverse learning needs of students in class.
• Stay current and responsive to changing developments in the profession and educational landscape through active engagement with industry and professional bodies/communities (in both domain-specific and teaching and learning)
• Maintain links with industry to stay current and to promote collaborations
• Propose, develop and participate in assigned outreach/community/industry activities.

You will also get the opportunity to work closely with other staff in developing business solutions through data pipelines.

At the same time, you will also get the opportunity to participate in action research and professional learning communities to enhance teaching practice.

[What we are looking for]

Relevant qualifications preferably in the field of Data Science, Data Engineering, Machine Learning, Statistics. You should have a minimum of 3 years industry experience, preferably in a related field. Teaching experience will be an added advantage.

Must have experience in one OR more of the following areas:

• Demonstrated ability in the application of Data Analytics/Data Engineering/Data Management/Machine Learning in real-world industrial settings with large scale data
• Experienced in distributed processing, database modeling, data pipelines, API design, optimization, modelling, big data, model implementation, data visualization
• Experienced working with the cloud (e.g. AWS, GCP, Azure)
• Experienced in data processing tools such as Spark, Beam, Flink; and with Hadoop Ecosystem such as ZooKeeper, YARN.
• Certification/Knowledge of data analytics tools like Microsoft Azure, IBM Watson, SAS, RapidMiner, KNIME, etc.
• Able to work independently as well as in a team, within tight deadlines (if applicable)

Genuine passion to share knowledge, mentor and interact with youths and adult learners, with strong communication and interpersonal skills.