Storytelling for more impactful data science


As data science teams look to scale their impact across the organization, data scientists often spend a long time optimizing and refining models. All too often, they end up neglecting what may be the most important selection criterion for scaling data science: acceptance by the end-user.

When presenting results, data teams often fall into the common pitfalls of communicating the impact of their work and are often met with skepticism towards the models they build and how they fit within the organization. This translates into decreased trust in data science, hyperfocus on edge-cases when scoping machine learning projects, and resistance to change or adopting data solutions. Getting everyone on board and earning a wide range of approval is often a critical step in successfully scoping, implementing, and evaluating models and their results.

In this webinar, we outline how storytelling enables data teams to bring the same facts to the table, but provide a clear framework that helps formulate the most impactful aspects of their work. We cover some tips and tricks using real case examples of how to convince the most skeptical end-users.

Key takeaways:

  • Storytelling is a core skill in the data teams' skillset

  • Storytelling in data science and machine learning can be just as factual as other presentation forms for communicating impact

  • Crafting audience-specific data stories increases the impact of data science within the organization

Gert De Geyter

Machine Learning Lead at Deloitte

Gert is based in New York where he works as machine learning lead for Deloitte Consulting. He is an invited professor for Python and machine learning at Toulouse School of Economics and School of Management. Gert holds a Ph.D. in Astronomy from Ghent University, where he focused on creating artificial intelligence programs to recreate 3D models of galaxies from 2D observed images.

Bhavya Dwivedi

Data Scientist at Deloitte

Bhavya is a data scientist in Deloitte Consulting where she works alongside clients to create value from data through her knowledge in machine learning and software engineering. Bhavya has the experience of applying supervised and unsupervised ML techniques, NLP, and deep learning to solve problems in domains such as healthcare, energy, finance, and insurance. She has a Masters of Computer Science degree from the Georgia Institute of Technology.

Adel Nehme

Data Science Evangelist at DataCamp

Adel is a Data Science educator, speaker, and Evangelist at DataCamp where he has released various courses and live training on data analysis, machine learning, and data engineering. He is passionate about spreading data skills and data literacy throughout organizations and the intersection of technology and society. He has an MSc in Data Science and Business Analytics. In his free time, you can find him hanging out with his cat Louis.

Connect with Adel on LinkedIn and Twitter.

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