• Job Type: Officer of Administration
• Bargaining Unit:
• Regular/Temporary: Regular
• End Date if Temporary:
• Hours Per Week: 35
• Standard Work Schedule:
• Building:
• Salary Range: $70,000-$80,000

Position Summary

The data engineer will help develop and maintain complex data infrastructure that is optimized for AI/ML research and applications to facilitate department-wide AI-related methodology research and their implementations across various public health initiatives within MSPH. The data engineer will be part of the team of the Translational AL Laboratory (TRAIL), collaborating with a diverse team of experts in biostatistics and contributing to its mission to transform public health research with AI/ML advancement.

Responsibilities

• 75% - Collaborate with academic researchers to support their AI/ML research and implementation needs, including but not limited to:
  * Design, construct, test, and maintain efficient and scalable local and cloud database management systems.
  * Develop recording systems, assuring that the flow of data is tracked accurately and timely.
  * Document all aspects of data management, such as database structure and related data cleaning procedures. Maintains data dictionary and metadata.
• 20% - Supporting the central functions activities of TRAIL, including but not limited to:
  * Conduct short consultations to recommend ways to improve data reliability, efficiency, and quality.
  * Support grant applications.
  * Assist with ethics review of human subjects research and preparation of IRB protocols.
  * Assist the TRAIL training sessions on modern AI-ready data infrastructure and engineering.
  * Participate in trainings identified for own career development.
• 5% - Other duties as assigned.

Minimum Qualifications

• Bachelor's degree in computer science, engineering, biostatistics, or other health data science-related fields. At least three years of data analytic and statistical analysis experience. Advanced education/degree may substitute for experience.

Preferred Qualifications

• Preferred Qualifications: Master's degree in computer science, engineering, biostatistics, or other health data science-related field. Experience with cloud services (AWS, Azure, Google Cloud) and API integration. Experience working with digital data in healthcare, e.g., electronic medical records, imaging data, billing or claims data, and some modeling experience to assess association or causation.

Other Requirements

• Proven ability with large data wrangling and analysis in R and/or Python (numpy, scikit, pandas), SQL, bash/unix scripting and high-performance computing.