I am primarily a research data analyst, with a focus on reproducibility and automation, to empower and support stakeholders into evidence-based decision-making.I particularly focus my skills on:- Turning raw data into a cohesive story, leveraging various statistical techniques to uncover relationships across metrics,- Providing user-friendly web-based applications to colleagues and stakeholders to access their data, and- Ensuring all data-handling and analytical steps are captured and fully reproducible. My toolbox mainly consists of R, along with Git, Github and Docker. Within the R ecosystem, I primarily rely on Posit's tidyverse, tidymodels, and Shiny set of tools, as well as Posit's RStudio IDE. Examples of deliverables I have provided to client by leveraging those tools include:- The production of multiple reports tailored to each organization's division on a pre-scheduled basis and have them automatically delivered to relevant stakeholders,- The creation of predictive models (whether they are linear frequentist, multi-level bayesian, or tree-based regression models), and store the engines within an API for production.Beyond the technical abilities, I pride myself in being able to explain difficult statistical concepts in ways that are easily understood to non-technical audiences. While I don't believe one needs to fully understand of the inner workings of a tool to use it, it is crucial to understand them at a conceptual level, and to recognize their strengths and limitations in order to prevent their misuse and abuse.