Sexual Health Researcher

Universities of Wisconsin•Madison, WI

3d•$75,000 - $85,000•Hybrid

About The Position

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. 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, in-person, or fully remote work arrangement. The initial term of this appointment is 2 years, with the possibility of being extended based on funding.

Requirements

Knowledge of sexual health, sexual violence, sex work and/or sex trafficking research
Strong background in quantitative statistics including: Data cleaning and wrangling Multivariate statistical analyses including regression Latent variable models including factor analysis and/or latent class analysis
Quantitative analytic skills in statistical packages, such as SPSS, STATA, R and/or MPlus
Excellent writing skills with regard to publication
Excellent written and verbal communication skills
Ability to remain highly organized, attend to detail, manage a variety of tasks, and meet required deadlines
Ability to work collaboratively with a diverse group of faculty, affiliates, staff, and students
Ability to work independently on set tasks
Ability to engage in creative and independent problem solving

Nice To Haves

Lived (personal) and/or work (professional) experiences or expertise related to sex work, sex trafficking, or providing SAMP
Prior research experience with sexual health, sexual violence, sex work and/or sex trafficking research
Experience with Latent Class Analyses

Responsibilities

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
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.
Assist in the preparation of annual progress reports, reports for the community, manuscripts, and community and peer-reviewed presentations