Job Description

Job Summary
The Institute for Research on Innovation and Science (IRIS) in the Survey Research Center at the University of Michigan's Institute for Social Research is looking for a Data Science Specialist to join the IRIS Research Support Team. You will work closely with other members of the team, and your primary responsibilities will be data development, analysis, and visualization; and support of internal and external researchers who are working with our data. You will bring robust technical expertise and research experience to our team.

Why Work at Michigan?
In addition to a career filled with purpose and opportunity, the University of Michigan offers a comprehensive benefits package to help you stay well, protect yourself and any eligible family members and plan for a secure future. Benefits include:

Generous time off
A retirement plan that provides two-for-one matching contributions with immediate vesting upon meeting eligibility requirements
Many choices for comprehensive health insurance
Life insurance
Long-term disability coverage
Flexible spending accounts for healthcare and dependent care expenses
Learn more about U-M benefits.

Responsibilities*
Data collection, retrieval, and management (35%)

You'll be responsible for working with IRIS Data Scientists to prepare and manage IRIS's research datasets. Specifically, you will:

Write scripts to download, ingest, and update large-scale publicly available datasets in a variety of formats (JSON, XML, Flat les, API calls) from multiple sources
Extract, transform, and load data into IRIS secure data warehouse
Perform quality assurance checks, describe, and document datasets
Prepare data for integration and for record linkage
Clean, harmonize, and de-identify IRIS data for research use
Build and maintain datasets for research use
Data analysis and visualization (35%)

You'll be engaged in hands-on data analytical work. Specifically, you will:

Write, maintain, and revise programs for data analysis
Demonstrate creativity in visualizing results, using Python, Tableau, or any other data visualization tools
Create rapid turn-around data summaries in response to ad hoc requests
Data structure and feature engineering for machine learning model development, training and testing using parallel processing in a high performance computing (HPC) environment.
Implement and evaluate shallow and deep machine learning models and classifiers using a range of supervised and semi-supervised techniques.
Perform quality assurance and validation checks and collaborate with researchers
Researcher support (30%)

You'll deliver high-quality research support to external researchers using IRIS data. Specifically, you will:

Contribute to data documentation and technical reports for IRIS research community
Provide technical assistance to researchers working in the IRIS virtual data enclave
Respond to research data questions
Assist researchers in le import into and export out of the IRIS enclave
Collaborate with IRIS technical and research staff to improve data quality, and address research community needs
Required Qualifications*
Bachelor's degree in Computer Science, Data Science, or a related field; or equivalent experience
1-2 years experience in programming and data analysis
Proficiency with Python for data science
Familiarity with relational databases, such as SQL
Desired Qualifications*
Experience preparing, updating, and documenting analytic datasets for a variety of statistical and computational techniques (e.g. network analysis, panel analysis, general multivariate statistical modeling)
Coursework or practical experience with computational and machine learning packages (e.g. PyTorch, DGL, Tensorow)