Data Scientist- Sr. Analyst

Company: The University Of Chicago
Location: Chicago
Posted on: May 28, 2023

Job Description:

Department -BSD PHS - Biostat Lab StaffAbout the Department -Public Health Sciences (PHS) is the home in the Biological Sciences Division to biostatistics, epidemiology and health services research. These core fields in public health research share a focus on the development and implementation of complex analytic methods to understand the determinants of health, the efficacy of experimental treatments, and the structure of health care at the population level. Bringing together these fields in one department underscores their commonality and enhances opportunities for interdisciplinary research. Faculty members lead local, national, and international studies, and also welcome opportunities to collaborate with faculty across the Biological Sciences Division and the university. Substantively, our research themes include social and environmental determinants of health, genetics and disease, the economics of health care, and the evaluation and implementation of new technologies in public health and clinical care. In terms of methodological expertise, areas in which our faculty has developed innovative approaches include: risk factor measurement; multilevel, clustered and longitudinal data; clinical trials; administrative health data; social networks; and statistical methods to assess the genetic and molecular basis of disease.Job Summary -The primary responsibility of the Sr. Data Scientist Analyst is to partake in research collaborations between the Biostatistics Laboratory and the Department of Neurology within the Biological Sciences Division. The successful candidate will not only be a thought leader on the data side of clinical research projects, working directly with scientists to leverage data to answer questions, but also have the technical ability to execute those plans. From exploring, summarizing, and manipulating data using common data science tools (Python and R primarily) to implementing machine learning algorithms on digital images and time series data, this job entails a wide range of data science activities. This job requires a candidate with a firm understanding of multiple data science activities as well as an ability to bootstrap knowledge around others.This at-will position is wholly or partially funded by contractual grant funding which is renewed under provisions set by the grantor of the contract. Employment will be contingent upon the continued receipt of these grant funds and satisfactory job performance.Responsibilities

• Builds predictive models using both machine learning as well as classical statistical techniques.
• Designs and executes statistical tests, as well as interprets the results.
• Manages data on a variety of research projects with several different data types (images, time series, relational databases, etc.).
• Implements machine learning and data management techniques in either R or Python.
• Knowledge of both machine learning as well as classical statistical techniques for developing predictive models.
• Performs complex ETL activities on a variety of different datasets.
• Generates reproducible data processing pipelines leveraging common data science tools.
• Writes technical documentation and user guides.
• Coordinates with research teams on data activities, establishing guidelines, setting deadlines and communicating results.
• Serves as a primary point of contact between researchers and outside technical resources.
• Analyzes moderatelycomplexdatasetsforthepurposeofextractingandpurposefullyusingapplicableinformation.
• Providesprofessionalsupporttostafforfacultymembersindefiningtheprojectandapplyingprincipals ofdata science in manipulation, statistical applications, programming, analysis andmodeling.
• Cleans,transforms,merges,andmatchesbetweenlargeandcomplexresearchandadministrativedatasets.Plans own resources to collect, organize, and analyze information from the University's various internal data systems as well as from externalsources.
• Buildsandanalyzesstatisticalmodelsandreproducibledataprocessingpipelinesusingknowledgeofbestpractices 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 QualificationsEducation:
  • Masters degree or higher in data science, statistics, computer science, or a related field.
  • Courses in machine learning and time series analysis. -Experience:
    • Working in an academic research environment.
    • Working with neuroscience research projects.
    • Three or more years experience using either Python or R for data analysis and management.
    • Familiarity with running jobs in a high performance computing environment.Technical Skills or Knowledge:
      • Strong Linux/Unix command line knowledge (including ssh).
      • Strong statistical skills including model building, interpretation, and using simulations to evaluate model performance.
      • Knowledge of data visualization principles and common libraries (plotly, ggplot, matplotlib, etc.).Preferred Competencies
        • ---Excellent communication skills, both oral and written.Working Conditions
          • Hybrid work arrangements will be considered.Application Documents
            • Resume/CV (required)
            • Cover Letter (preferred)When applying, the document(s) MUST -be uploaded via the My Experience page, in the section titled Application Documents of the application.Job Family -ResearchRole Impact -Individual ContributorFLSA Status -ExemptPay Frequency -MonthlyScheduled Weekly Hours -40Benefits Eligible -YesDrug Test Required -NoHealth Screen Required -NoMotor Vehicle Record Inquiry Required -NoPosting Statement -Employees must comply with the University's COVID-19 vaccination requirements. More information about the requirements can be found on the .The University of Chicago is an 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 Staff Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via 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: -. -Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.

Keywords: The University Of Chicago, Chicago , Data Scientist- Sr. Analyst, Professions , Chicago, Illinois