Analytical Voyages #3: Exclusive Interview with Ariel Herrera

Welcome to another post in our series “Analytical Voyages” on Data Science Journeys, where we delve into the experiences and insights of professionals who have carved their paths in the field of data science. In this edition, we had the privilege of conversing with Ariel Herrera, an experienced Data Scientist with a demonstrated history of working in the financial services and SaaS industry. Ariel's passion is deriving insights from large datasets and effectively communicating results to a non-technical audience.

Key Highlights from the Interview

1. The Power of Automation: Ariel's career journey took a significant turn when she discovered the power of automation through coding. This realization, triggered by a VBA course, ignited her passion for programming and set the stage for her transition into the data science field.

2. Continuous Learning: Throughout her journey, Ariel consistently sought opportunities for learning and growth. She pursued a Master's Degree in Information Systems, honing her skills and deepening her knowledge in data science and technology.

3. Consulting and Stakeholder Communication: Ariel's experience in consulting taught her the art of effectively communicating complex technical concepts to senior management. This skill proved instrumental in her ability to propose and implement data-driven projects that impact the business positively.

4. Networking and Collaboration: Building a strong professional network was a key strategy for Ariel. Regularly connecting with colleagues and seeking advice from others in her field allowed her to tap into valuable resources and insights.

5. Real-World Problem Solving: Ariel's advice for aspiring data scientists is to tackle real-world problems they are passionate about. Her own journey into real estate analytics exemplifies this approach, where she leveraged data to automate property assessment and shared her work through a public repository and blog.

In Ariel's inspiring career journey, we see the transformative power of automation, the importance of continuous learning, effective communication, networking, and the value of solving real-world problems. Her story serves as a testament to how passion, skills, and dedication can lead to a successful and impactful career in the dynamic field of data science.