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Technical Associate I, FSAS
  • Job Number: 25719
  • Functional Area: Research - Other
  • Department: MIT Sloan FSAS
  • School Area: Sloan School of Management
  • Pay Range Minimum: $50,000
  • Pay Range Maximum: $63,000
  • Employment Type: Full-time Temporary (Hybrid)
  • Employment Category: Exempt
  • Visa Sponsorship Available: No
  • Schedule:
  • Pay Grade: No Grade


Posting Description

TECHNICAL ASSOCIATE, FSAS, MIT Sloan FSAS, will help create an extensive ETL [Extract, Transform, Load] pipeline to process numerous datasets. The individual will identify and vet data sources; develop pipelines to robustly extract, process, load, and validate data; develop data products such as violation risk scores and product classification; and performing and write up research on these data products. Data sources are in multiple languages and include both structured and unstructured data. Working as part of the Data Science subgroup, the Technical Associate I will collaborate closely with interdisciplinary teams to ensure data quality, consistency, and usability across the project. The role will also involve conducting exploratory analyses, supporting model development, and contributing to written research outputs, including technical documentation and reports.  This position offers an opportunity to contribute to high-impact research at the intersection of data science, food safety, and public health, while gaining experience with complex, real-world datasets and advanced analytical methodologies.

A full job description is available at https://web.mit.edu/sloan-hr/jobs/TechnicalAssociateIFSAS.pdf

Job Requirements

REQUIRED: Bachelor’s degree in a relevant scientific field (computer science, engineering, mathematics); a minimum of two years of specialized experience with qualitative data analysis, research methods, social sciences (which may include experience gained as an undergraduate); familiarity using Python and SQL; familiarity using Github; ability to work both independently and as a member of a team; attention to detail; and familiarity with basic statistical techniques (e.g. hypothesis testing, simple linear models). PREFERRED: Experience working with databases (MSSQL); experience working with Docker; experience working with Selenium; experience working with machine learning (TensorFlow); and an interest in food safety and security issues.

This is a one-year term position with full benefits.

5/15/2026