The Data Standard

Student challenges in the data science world with Chester Ismay
Chester Ismay, Director, Data Science Education at Flatiron School, sits down with TDS to discuss student challenges in the data science world.

Episode Summary

Organizations across the globe are looking to organize, process and unlock the value of the torrential amounts of data they generate and transform them into actionable and high-value business insights. Hence, hiring data scientists – highly skilled professional data science experts have become supercritical. Today, there is virtually no business function that cannot benefit from them. In fact, the Harvard Business Review has labeled data science as the “sexiest” career of the 21st century. However, no career is without its own challenges, and being a data scientist, despite its “sexiness” is no exception.
Despite all the challenges, data scientists are the most in-demand professionals in the market. With the data world changing at a rapid pace, being a successful data scientist is not just about having the right technical skills but also about having a clear understanding of the business requirements, collaborating with different stakeholders, and convincing business executives to act upon the analysis provided.

If you’re a student or beginner facing challenges in the data science world and would like to learn more about overcoming them, then this podcast is for you as our guest Chester Isamay sits down with us to discuss challenges in the data science world.

Meet The Host

Catherine Tao

Data scientist at The Data Standard

Catherine Tao is a tech enthusiast looking for new methods for building connections with businesses around the world. Her extensive knowledge of data science allowed her to develop new solutions and implement them into existing ecosystems. She is currently working as a Data scientist and Exclusive Podcast Producer at The Data Standard.

Meet The Guest

Chester Ismay

Director, Data Science Education at Flatiron School

Experienced Data Scientist and manager with a demonstrated history of working in academia, consulting, and e-learning solving real-world problems. Skilled in teaching Statistical Modeling, Machine Learning, R, Python, SQL, Mathematics, Computer Science, and Sociology. Strong leader with a Doctor of Philosophy (Ph.D.) in Statistics from Arizona State University. Focused on improving data science education through taking action and growing through mistakes, collaboration, and compassionate communication.