Sexual Health Researcher

Current Employees:
If you are currently employed at any of the Universities of Wisconsin, log in to Workday to apply through the internal application process.
Job Category:

Academic Staff

Regular

Data Scientist II

• Documents approaches to address research questions and contributes to the establishment of reproducible research methodologies and analysis workflows

• Independently identifies and implements appropriate data science techniques to find data patterns and answer research questions chosen by the lead researcher including data visualization, statistical analysis, machine learning, and data mining

• Composes and assembles reproducible workflows and reports to clearly articulate patterns to researchers and/or administrators

• Organizes and automates project steps for data preparation and analysis

• Prepares data sets for analysis including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources

We are seeking a Data Scientist to become an integral team member and collaborator on the development, design, and implementation of a community-engaged, mixed methods research project funded by the National Institute of Child Health and Human Development. The Data Scientist will primarily conduct analyses and disseminate findings within research team led by Drs. Lara Gerassi (PI) and Kate Walsh (co-I).

The project used rigorously developed, adapted, and tested Sexual Acts and Materials for Pay or Compensation (SAMP) measure to understand the prevalence and characteristics of young adults (ages 18 to 34) who report SAMP. At the time of hire, the Data Scientist will primarily work on the second and third specific aims of this 5-year, community-engaged project. First, we will identify the prevalence and associated characteristics (e.g., adverse experiences, substance use, mental health problems, harm reduction strategies, and violence) of SAMP in a nationally representative, probability-based sample (Amerispeak) of young adults (ages 18-34) using our adapted measure.

We will (a) report the prevalence of sex trading, (b) use Latent Class Analysis (LCA) to examine typologies of those who report providing and considering sex trading and their reasons for doing so, and (c) examine associated health consequences and financial characteristics. Second, we will examine the characteristics of SAMP in a non-probability sample of young people who report having participated in at least one sex trading behavior (ages 18-34).

We will use web-based, Respondent Driven Sampling (webRDS) to recruit this hard-to-reach population and replicate and extend aim 2’s LCA to understand differences and similarities in sex trading among young adults who report providing different types of sex trading acts, as well as those who endorse particular types and report considering others. Findings will result in a comprehensive understanding of SAMP and consequences in the United States, which is needed to inform prevention and intervention strategies to reduce harm.

In this role, you can expect to:

• Lead data cleaning and documentation procedures under the direction of PI and co-Is
• Analyze complex research data sets including nationally representative samples and community driven, non-representative samples
• Execute analytic plans to identify national prevalence estimates of SAMP and identify harm increasing and reducing circumstances of SAMP
• Conduct Latent Class Analyses and general multivariate statistics (e.g., regression) across multiple samples.
• Organize and document analysis code for research transparency, standardization, and replication
• Support and prepare documents in accordance with data sharing procedures as required by funder
• Support administrative processes related to participant compensation and other tasks related to the project’s grant.
• Supervise research specialist/project coordinator on tasks to support this grant-funded project
• Assist in the preparation of annual progress reports, reports for the community, manuscripts, and community and peer-reviewed presentations

Local candidates may choose to work in a hybrid,…