Many times, data scientists can fall into the trap of resume-driven development. As in, learning the shiniest, most advanced technique available to them in an attempt to solve a business problem. However, this is not what a learning mindset should look like for data teams.
As it turns out, taking a step back and focusing on the fundamentals and step-by-step iteration can be the key to growing as a data scientist, because when data teams develop a strong understanding of the problems and solutions lying underneath the surface, they will be able to wield their tools with complete mastery.
Ella Hilal joins the show to share why operating from an always-learning mindset will open up the path to a true mastery and innovation for data teams. Ella is the VP of Data Science and Engineering for Commercial and Service Lines at Shopify, a global commerce leader that helps businesses of all size grow, market, and manage their retail operations. Recognized as a leading woman in Data science, Internet of things and Machine Learning, Ella has over 15 years of experience spanning multiple countries, and is an advocate for responsible innovation, women in tech, and STEM.
In this episode, we talk about the biggest mistakes data scientists make when solving business problems, how to create cohesion between data teams and the broader organization, how to be an effective data leader that prioritizes their team’s growth, and how developing an always-learning mindset based on iteration, experimentation, and deep understanding of the problems needing to be solved can accelerate the growth of data teams.
