Research Assistant (Software Engineer)

Overview

We are looking for people with a strong background in Computation & data infrastructure and/or building data systems. They must be comfortable working with a range of stakeholders and functional teams including Students, Faculty, IT, and External Collaborators. The right candidate will have a passion for working with numerous small research teams to assist in managing their infrastructure needs and advise them on best practices to engineer their projects efficiently.

Responsibilities

INFRASTRUCTURE MANAGEMENT (50%):

1. Maintain servers, including file, web, and proxy servers, including security patches.
2. Allocate compute/storage resources as needed.
3. Analyze institute infrastructure needs to implement services providing improvements to systems.
4. Manage the Institute Website.
5. Liaise with Global IT teams to ensure compliance with their policies and be a single point of contact for the institute for troubleshooting.
6. Manage recording and streaming systems during regular seminars, conferences, and workshops.

DATA ENGINEERING (25%):

1. Support research teams with advice on efficient Data Engineering practices including automation of data pipelines, data cleansing, integrity checks, etc.
2. Develop processes to handle remote data access/management in compliance with security best practices (and appropriate policies).
3. Assess the effectiveness and accuracy of new data sources and data gathering techniques.

SYSTEM DEVELOPMENT (25%):

1. Create APIs to integrate data sources into functional blocks of software & services.
2. Create APIs for downstream usage of Data models.
3. Coordinate with different functional teams to implement models and monitor outcomes.
4. Promote security best practices for application development.

Requirements

1. Bachelor's degree in Computer Science, Operations Research, or Engineering with more than 3 years of relevant experience.
2. Experience in maintaining virtualized server infrastructure and creative problem solving within large IT infrastructure.
3. Deep understanding of statistical analysis, data mining, or machine learning.
4. Practical experience in working with large structured and unstructured data sets.
5. Ability to think analytically and deliver results that drive business decision making.
6. Team player to build strong partnerships.
7. Competency in one or more of the programming languages or tools: Python, R, Spark.
8. Experience in security engineering will be a plus.
9. Experience or knowledge in AWS/GCP environment will be a plus.
10. Prepared to take on new challenges and ad-hoc requests that need a quick turnaround.
11. Excellent written and verbal communication skills for coordinating across teams.