Research Assistant

Description:

The Data Analytics Research Assistant - Economics will be supervised by Professor Samreen Malik and will be part of a team that provides Malik’s team of researchers and faculty with Data Analytics, Data visualization, Data Management, coding & development and support of research design.

As part of Malik’s team, there will be hands on experience to learn research methods, experimental designs and tools specifically applied to research in social science. Working with Dr. Malik and her team to advance their research work by providing Data analytics and research analysis support. Assist researchers with Data management including big data, data mining and database support and development. Support and advise researchers on Data visualization. Working with faculty and researchers to support researchers programming in STATA, and use AI including Machine Learning. Support researchers with coding and algorithm development. Conduct training, engagement with students for senior thesis (graduate and undergraduate level).

Breadth of Responsibility

• Lead day-to-day research support in the areas of Data Analytics, Data visualization and Data management.
• Support researchers and faculty with their coding and algorithm development.
• Support Dr. Malik and her researcher team with their use of Machine Learning and AI.
• Provide student mentorship, consultancy and training on areas related to Data analytics, visualization and management.
• Collaborate with Dr. Malik’s team on large analytical and data intensive projects.
• Make technical decisions consistent with NYUAD compliance and architectural requirements and to manage customer issues, respond to support queries related to usage/utilization, application installation, and configuration, tuning and running issues
• Provide technical leadership and support Research projects. Ability to clearly communicate technical concepts to non-technical audience. Excellent organizational and communication skills.

Required Education

Bachelor’s degree 2 years’ experience (or educational equivalent) in Computational Science, Statistics, computational social science or equivalent