I learned coding because I understood the value of understanding technical languages, especially when with working with digital products.

In 2017, I started learning HTML5, CSS3, JavaScript, jQuery, Bootstrap, and PHP. I can say with confidence that I know HTML5 and CSS3 well enough to code and develop efficiently for front-end. As for the other languages, I have some familiarity with it now.

I also learned programing using Python, where I learned Python basics, simple programs, and structured types, and good programming practices. I am not equipped enough to code Python for professional work, however, I have some familiarity with it.

As part of my Master's program at Penn, I completed training in Quantitative Modeling and Data Science (Machine Learning) in R. I am proficient enough in R to run predictive models, sentiment analyses, network analyses, statistical analyses, and data visualizations.

🧠 How my technical background makes me a strong applied behavioral scientist:

• I can understand developers - how they think and speak. While I do not have engineering experience, I found that my technical knowledge helps me communicate much more effectively with technical teams. I'm also able to understand some of the struggles developers go through. I have successfully written technical requirements and product rules that were clear and logical for backend engineers to understand.

• I have an understanding of what features are technically practical or not. While I'm not an engineer or data scientist by trade, when I'm ideating features for a. product, I can assess what can be feasible and how to best ideate the feature so it can be implemented. This makes me resourceful if I'm collaborating with the team on ideas.

• I can be agile in creating and deploying digital solutions, providing quick and efficient approaches to testing hypotheses, modifying front-end implementations, or iterating on digital solutions. 

💰 How my technical background adds value your team:

• You have someone who can be the bridge between product and engineers - and understands how to create clear technical requirements and product rules that are logical and systematic.

• You have someone who thinks in structured, logical ways, breaking complex problems into smaller, testable components - a mindset that directly applies to behavioral science.

• You have someone who can ideate and design in an innovative way - who has some data science background knowledge and how to ideate that for a product feature.