The USF Data Science Podcast: Who It's For and Who Sponsors It

Est. audience: 400
Apple rating: 5 from 3
Cadence: Monthly
Latest: 2026-08-19
By: Robert Clements
Based on: 12 recent episodes

Covers: Data science practices, machine learning models, statistical methods, exploratory data analysis, and career development in data.
For: Data scientists, machine learning engineers, and data professionals navigating technical roles.
Best for: Aspiring and practicing data professionals seeking technical advice and industry insights.
Skip if: General business leaders looking for non-technical strategy or high-level executive management content.

Start with

Storytelling: Leveraging your EDA knowledge: Explains how to transform exploratory data analysis into actionable narratives for stakeholders.
Lessons Learned from Advanced ML’s Kaggle Competition: Covers feature engineering, handling dimensionality, and technical decisions in machine learning models.
Product Data Science at Microsoft with Kekona Sorenson: Discusses improving products through data analysis, experimentation, and building a data-driven culture.

Summarised by AI from 12 recent episodes. Audience estimate and Apple rating from Podscan, checked 2026-11-03; treat the estimate as a guide and ask the show for its own numbers. Prices are not included. Report a mistake.