Research Associate, Personnel Health Research & Data Analytics

Research Associate:
Personnel Health Research & Data Analytics, Military (Washington, D.C.)

At Fors Marsh, we take on issues that matter. We are a team of researchers, strategists, and communicators working together to drive lasting change. We look at human behavior from all angles with a deep understanding of people and context to design solutions that influence decision-making and move people to action. Our work promotes health and well-being, shapes resilient communities, and builds effective and accountable institutions.

We are a certified B Corporation and a Top Workplace for 7 consecutive years.

Fors Marsh is seeking an intelligent and motivated researcher with a background in quantitative social science. This individual's primary responsibility would be to support a portfolio of quantitative social science and data science research projects for our Personnel Health Research & Data Analysis team. This individual would work in a researcher role, providing assistance on projects focused on improving service members' well-being, advancing data science insights, and inform policies and organizational decision making.

This job is best for someone who enjoys applying innovative methods to solve challenging analytic problems, has experience working with large data sets, and thrives in a collaborative environment.

Responsibilities include:

• Conducting exploratory data analysis, cleaning (e.g., data transformations), and analysis on large-scale data
• Executing advanced statistical techniques such as multi-level modeling (e.g., cross-classified random effects, linear mixed effects), data reduction (e.g., PCA, factor analysis, clustering), predictive model selection (e.g., LASSO, Ridge), natural language processing, and/or machine learning techniques
• Executing data visualization techniques and dashboard creation steps
• Supporting all phases of the data science and social science analytics process, including the analysis and interpretation of survey research, integrating datasets (e.g., survey data integrated with administrative data), and other studies
• Supporting and executing survey workflows focused on population specification and sample frame development, including identifying relevant data sources, cleaning, deduplication, and frame quality checks
• Resolving problems that require general knowledge of analytic methodologies and principles, as well as the ability to learn new techniques
• Communicating trade-offs associated with analytic approaches to technical and non-technical audiences.
• Conducting quality checks on data extracts, analyses, and deliverables
• Working in R and Python to execute automation tasks, R package creation, data wrangling, exploratory data analysis, and executing advanced analyses
• Working in or learning Databricks

Team orientation:

• Work under supervision of a Senior Team member
• Work collaboratively with a mixed team of data and social scientists to operationalize personnel-related metrics and explore, aggregate, and analyze large, complex quantitative data sets through a variety of techniques.

Client and stakeholder interaction and communication:

• Assist with briefing clients and stakeholders under supervision from Senior Team members
• Assist in preparing research reports/briefs for technical and non-technical audiences, and other internal or external communications summarizing research methods, findings, and implications.

Qualifications:

• Degree in a heavily quantitative social science (e.g., sociology, political science, psychology), data science, or related field;
  Master's preferred
• Master's degree with 2+ years of applicable industry experience;
  Bachelors degree with 4+ years of applicable industry experience
• Experience conducting quantitative research, in particular leveraging advanced statistical modeling techniques
• Working knowledge and experience of quantitative methodologies such as multi-level modeling, data reduction techniques, and natural language processing
• Experience working with diverse data sources, including survey, personnel, and administrative data
• Working knowledge of survey workflows supporting population definition, sample frame construction, and feature table creation to assist…