Not Your College Stats Course: Engaging Stakeholders Through Data Science
NYR Conference
When working in industry data scientists must collaborate with colleagues across many different positions. You need to understand stakeholder needs and communicate results with non-technical teams. While you don't need to share the mathematical details, explaining analyses builds a stronger relationship with stakeholders and helps them to understand the data science process. How do you determine the best way to deliver results? What are some techniques you can use to break down data science techniques and algorithms? This talk will review methods to effectively share data science analysis and why it is important to stay aligned with stakeholders.
Creating Production Level Data Science Code
NYR Conference
A data scientist writes code throughout every stage of a project from exploratory data analysis to evaluating models and summarizing results. Once you've developed a proof of concept or minimally viable product it can be a daunting task to put it into production. How do you organize and adapt all the code that you created? What can you do to make sure the code catches errors and alerts you to them? Do you feel overwhelmed by everything you need to do? By attending this presentation you will learn tips and strategies to organize your own code during a project to make creating production code easier. You will also learn how to optimize your code to catch errors and create effective documentation.
Ace the Data Science Interview
Women in Data Science - UNC Charlotte
How do I prepare for the technical portion of an interview? What are the most important skills to highlight during my interview? I don’t have any full-time work experience – what can I talk about to show that I’m a great fit for the role? How can I reduce my nerves? In this live virtual presentation, you will the learn skills and strategies to address these common interview stressors so that you can walk (or Zoom) into your next data science interview with confidence and poise.
This talk will cover what one can expect from the data science interview process and how to prepare for the different types of questions that commonly occur. The presentation contains examples of these typical interview questions and will discuss ways to answer them so that you highlight your skills and experience. Your technical skills and training are not the only things that companies look for, and this talk will cover how you can discuss your experiences outside of data science to demonstrate other qualities that companies seek.
Three Lessons from Three Years of Data Science
Data Umbrella, Pyladies NYC
This talk highlights three important lessons Megan has learned in the first three years of her data science career. Tune in for lessons on project management, communication and tips on advocating for yourself.
Exploring Data Science
New York University - Social Psychology Graduate Program