Data Science Analyst

Department
 

BSD SUR - Section Administrator: OHNS - Thirty Million Words: Research Analysis

About the Department
 

The TMW Center for Early Learning + Public Health (TMW Center) is a joint venture between The University of Chicago Biological Sciences Division and the Division of the Social Sciences. It 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 for healthy brain development, however there are no universal and standardized measurement tools capable of quantifying the quality of these environments at scale and with high accuracy. Access to this type of data could allow caregivers to enhance children’s language environments in real-time, give policymakers insights into how to design policies that have a population-level impact, and advance the science of early skill formation. To fill this gap, the TMW Center is developing an AI-driven wearable device to reliably and accurately assess children’s early language environments at home or at school. Our device is like a ‘Fitbit’ for child development; it will be connected to a smartphone app that will provide personalized, real-time feedback to empower parents and educators to create the best language environment for their children. We are looking for a talented data scientist to join our team and help us build high-quality algorithms for the development of the device. Previous experience and coursework in machine learning and Python are necessary.

Job Summary
 

We are seeking candidates with experience and interest in computer science, machine learning or data science. This is a unique opportunity and the data scientist could work across a range of areas, including but not limited to development, design, search, platform, test, quality, big data, front end, and back end.

Responsibilities

• Codes high-volume and scalable software.

• Builds and develop new user-facing experiences/visualizations.

• Builds tinyml or deep learning nideks.

• Assists in analyzing data for the purpose of extracting applicable information. Performs research projects that provide analysis for a number of programs and initiatives.

• May assist staff or faculty members with data manipulation, statistical applications, programming, analysis and modeling on a scheduled or ad-hoc basis.

• Collects, organizes, and may analyze information from the University's various internal data systems as well as from external sources.

• Maintains and analyzes statistical models using general knowledge of best practices in machine learning and statistical inference. Performs maintenance on large and complex research and administrative datasets. Responds to requests and engage other IT resources as needed.

• 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.

---
Work Experience:

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

---
Certifications:

---

Preferred Qualifications

Education:

• Master’s degree in Computer Science or related field from an accredited college or university.

Technical Skills or Knowledge:

• Large-scale tools: Spark or Dask (rapids.ai is strongly preferred).

• Core ML: Jupyter, Scikit-learn, Numpy, Pandas.

• NLP Tools: Spacy, NLTK or CoreNLP.

• Deep learning frameworks: Tensorflow or Pytorch (strongly preferred).

• Linux command line experience, High-Performance Computing HPC experience (strongly preferred).

• Experience with Deep Learning Video and Image Analysis.

• Experience with cloud resources such as Amazon Web Services.

Preferred Competencies

• Analytical skills.

• Problem-solving skills.

• Attention to detail.

• Organizational skills.

• Verbal and written communication skills.

• Work independently and as part of a team.

Application Documents

• Resume (required)

• Cover Letter (required)

When applying, the document(s) MUST  be uploaded via the My Experience page, in the section titled Application Documents of the application.

Job Family
 

Research

Role Impact
 

Individual Contributor

FLSA Status
 

Exempt

Pay Frequency
 

Monthly

Scheduled Weekly Hours
 

40

Benefits Eligible
 

Yes

Drug Test Required
 

No

Health Screen Required
 

No

Motor Vehicle Record Inquiry Required
 

No

Posting Statement
 

Employees must comply with the University’s COVID-19 vaccination requirements. More information about the requirements can be found on the University of Chicago Vaccination GoForward .
The University of Chicago is an Affirmative Action/ Equal Opportunity/Disabled/Veterans Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national or ethnic origin, age, status as an individual with a disability, protected veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

 

Staff Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

 

We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages a diversity of perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange.

 

All offers of employment are contingent upon a background check that includes a review of conviction history.  A conviction does not automatically preclude University employment.  Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

 

The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at: http://securityreport.uchicago.edu . Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.