Data Scientist, Sr. Analyst

Department
 

BSD DFI - Translational Informatics

About the Department
 

The Duchossois Family Institute (DFI) at the University of Chicago is using cutting-edge technologies and developing facilities to accelerate research and introduce novel interventions that optimize microbiome-mediated host defenses, with the goal of enhancing health. By developing new knowledge about the interactions between the human body and the microbiome, the DFI is breaking new ground that will lead to therapies that increase resistance to a wide range of diseases.

Job Summary
 

The Duchossois Family Institute focuses on the role of commensal bacteria in enhancing disease resistance and is using genomic and metabolomic platforms to characterize the microbiome and its metabolites. At DFI, we rely on a dynamic team of programmers, data scientists and engineers to handle our rapidly growing biomedical data. We are seeing a full-stack data engineer who will work with new technologies and architectures to develop scalable analytical applications that will help in organizing, managing, and extracting meaningful inferences for a better understanding of the data. Experience with biomedical data and computational expertise is required to build custom inward and outward facing applications with advanced AI/ML approaches and robust visualization. The ideal candidate has experience building products across the stack and a firm understanding of web frameworks, APIs, databases, visualization frameworks, and multiple back-end languages. The Data Science, Sr. Analyst. will work as part of a translational informatics team.

Responsibilities

• Participate in agile software development, including design, implementation, and deployment.

• Design and develop robust and reusable visualization components using advanced Web technologies and frameworks.

• Designing and implementing scalable web services, applications, and APIs to facilitate better understanding of all the biomedical data generated at the DFI.

• Contribute to the development of an integrated knowledgebase (Relational Database) integrating different omics data types and clinical data.

• Transforming data into new formats to make it more appropriate for analysis.

• Has working knowledge of multiple programming languages and statistical packages, as well as knowledge of dataset tools and Artificial Intelligence/Machine Learning (AI/ML) tools.

• Develop Python and JavaScript libraries for the visualization of microbiome, metagenome, metabolome and other biomedical data types generated at the DFI.

• Work in collaboration with others to complete projects in a timely and efficient manner.

• Support scalable bioinformatics workflows for the end-to-end data analysis of high throughput microbiome, metabolome, and clinical data.

• Customize existing applications to meet specific scientific project needs.

• Assist in creating data algorithms and specialized computer software to identify and classify components of a biological system (e.g. DNA and protein sequences).

• Support the development of data models, databases, and software applications.

• Produce, present, and discuss high quality data analysis reports.

• Participate in the communication of results through scientific publications.

• Develop domain-specific languages to describe bioinformatics workflows.

• Run parallelizable big data workflows on cloud platforms such as AWS, Azure, Google.

• Automate the deployment of DFI APIs and web applications using Docker and other CI/CD technologies.

• Participates in creating data algorithms and specialized computer software to identify and classify components of a biological system (i.e. DNA and protein sequences).

• Applies basic application of computational tools and information technology to gather, analyze and visualize data in biology and biomedical research.

• Interprets data analysis of high throughput microbiome, metabolome, genetic and other biomedical data.

• Plans own resources to implement or modify existing web-based applications.

• Analyzes moderately complex data sets for the purpose of extracting and purposefully using applicable information.

• Provides professional support to staff or faculty members in defining the project and applying principals of data science in manipulation, statistical applications, programming, analysis and modeling.

• Builds and analyzes statistical models and reproducible data processing pipelines using knowledge of best practices in machine learning and statistical inference. Serves as a single point of contact for all requests and engages other IT resour