Daniela Trespalacios

Hometown

Bogotá, Colombia

Current city

Bogotá, Colombia

What is your current job?

HP Inc, Center of Excellence Sales Analytics, Data Scientist

What were you doing before you started the master’s program?

I worked for the Latin American Sales Team at HP inc, performing multiple data analyses and project evaluations.

What were the top 1-3 factors that went into your decision to choose the MS in Applied Data Science Program at UChicago?

Professor’s experience, Curriculum, The University ranking position

What was one of your favorite aspects of being a student at UChicago?

I had the opportunity to connect with professors with an outstanding experience. I also met extremely talented people from different countries and backgrounds which led me to increase my professional network and get a better understanding of different cultures.

In your view, how has the MS in Applied Data Science degree advanced your career so far?

This degree helped me gain visibility within my professional network and it allowed me to advance from an analyst position in a sales team to a global data science team.

What was one of your favorite classes you took at UChicago and why?

Machine Learning because I had the chance to deepen my knowledge of advanced ML algorithms and apply them to real use cases. Yuri Balasanov provided great guidance and resources to understand these advanced topics.

What advice would you give to prospective students who are seeking a master’s degree in data science?

Ask as many questions as you can, especially if you could link those questions with real-world cases or examples.

What do you enjoy doing outside of work?

I enjoy reading Latin American literature.

What excites you right now about the field of data science?

This field allows me to solve business problems with multiple possibilities of methodologies that range from simple descriptive analysis to complex modeling pipelines.

What is one piece of advice would you give to prospective students?

Always keep in mind that behind a data science solution, there is a context or business problem. If you can’t answer what is the problem you’re trying to solve or the purpose of any analysis, you need more time to understand the context, instead of making the solution more complex.