This job was posted by https://illinoisjoblink.illinois.gov : For more information, please see: https://illinoisjoblink.illinois.gov/jobs/11880028 Department

BSD SUR - OHNS: Thirty Million Words - Tech

About the Department

The TMW Center for Early Learning + Public Health (TMW Center) develops science-based interventions, tools, and technologies to help parents and caregivers interact with young children in ways that maximize brain development. A rich language environment is critical to healthy brain development, however few tools exist to measure the quality or quantity of these environments. Access to this type of data allows caregivers to enhance interactions in real-time and gives policy-makers insight in how to best build policies that have a population-level impact. The ECM team within TMW Center in partnership with Schmidt Futures is building a low-cost wearable device that can reliably and accurately measure a child\'s early language environment vis--vis the conversational turns between a child and caregiver. The goal is to provide accurate, real-time feedback that empowers parents and caregivers to create the best language environment for their children.

Job Summary

The TMW Center is looking for a Data Science Analyst to support the wearable team in the development of this wearable technology. As a member of the TMW Center\'s wearable team, the Data Science Analysts will develop, test, and validate existing machine learning algorithms, train new algorithms, lead ETL efforts, and partner with other team members and vendors to connect the algorithm, hardware and firmware pieces together. The TMW Center seeks candidates who are dynamic, collaborative, and curious.

Responsibilities

• Define features of audio recording to develop novel models.
• Create cutting-edge machine learning algorithms on audio datasets.
• Develop scripts and code for analyses.
• Analyze moderately complex data sets for the purpose of extracting and purposefully using applicable information.
• Build and analyze statistical models and reproducible data processing pipelines using knowledge of best practices in machine learning and statistical inference.
• Supervise contributions of specialized Student Research Assistants to prepare datasets to train algorithms.
• Assist Chief Technology Officer on a weak supervision pipeline.
• Collaborate with team and external vendors (hardware, firmware, electrical engineers) and weigh in on requirements to run the algorithms.
• Keep abreast of broader tech and data systems landscape and best practices; secure and maintain needed certifications to ensure proper creation and maintenance of TMW Center data systems.
• Ensure secure data storage, guaranteeing regular backups and storage in compliance with HIPAA and current best practices.
• Cleans, transforms, merges, and matches between large and complex research and administrative datasets. Plans own resources to collect, organize, and analyze information from the University\'s various internal data systems as well as from external sources.
• 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 resources to assist as needed. May partner with other campus teams to assist faculty with data science related needs.
• Performs other related work as needed.

Minimum Qualifications

Education:

Minimum requirements include a college or university degree in related field.

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Work Experience:

Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

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Certifications:

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Preferred Qualifica ions

Education:

• Advanced degree in Computer Science, Statistics, Mathematics, or Economics with a focus on computer science.

Experience:

• Experience with Arduino or hardware integration.
• Experience developing and implementing machine learning solutions for real world use.
• Experience with cloud resources such as Amazon Web Services (including AWS Redshift, Amazon RDS, and Amazon Aurora).
• Experience using Linux.

Preferred Competencies

Proficiency in Python, Numpy, Pandas and scikit-learn.

Familiarity handling terabyte size datasets.

Ability to write production-level code.

Ability to handle multiple tasks and assignments simultaneously.

Problem-solving skills, including a strong ability to prioritize and collaborate.

Excellent verbal and written communication skills.

Proven ability to establish and stick to timelines.

Excellent organizational skills, including strong attention to detail.

Knowledge of university and research-related re