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HBO and The Ringer's Bill Simmons hosts the most downloaded sports podcast of all time, with a rotating crew of celebrities, athletes, and media staples, as well as mainstays like Cousin Sal, Joe House, and a slew of other friends and family members who always happen to be suspiciously available.
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In this episode of AI Lab Unfiltered, Drew and Pete sit down with Shannon McCormick, Senior Data Scientist at Scandinavian Tobacco Group, to talk about what it really looks like to unleash AI inside your datasets and treat it like a smart coworker instead of a magic black box.
Shannon walks through how she uses transactional and customer data in a B2C environment to drive better decisions across shipping, promotions, and retention—everything from scorecards and customer profiles to advanced predictive models with millions of rows. They dig into the messy realities of the job: why 70% of her time is still spent in SQL, why “garbage in, garbage out” still rules, and why you shouldn’t wait for perfect data before you start experimenting with AI.
They also unpack the difference between LLM-powered analysis and classic machine learning, when a simple logistic regression beats building your own LLM, and how tools like Copilot and ChatGPT can extend (not replace) the skills of data scientists, marketers, and engineers. The conversation closes with a hopeful look at AI as a creator of new jobs, new businesses, and a radically lower barrier to entrepreneurship.
If you’ve ever wondered how to actually use AI with your business data—without getting lost in the hype—this episode is your playbook.
Chapters
- (00:00) Cold Open, Sponsor Shoutout & Episode Setup
- (01:35) What Does a Data Scientist Actually Do?
- (02:56) Inside B2C Data: Transactions, Shipping & Promotions
- (05:54) Predictive Marketing Models & Campaign Targeting
- (08:33) Analytics Beyond Big Tech: Meijer, Cigars & Mid-Sized Teams
- (10:42) Data Quality, Cleaning & “Tending the Data Garden”
- (13:54) Influencing Data Collection & Working with Data Engineering
- (14:58) Synthetic Data, Surveys & Learning from What You Don’t See
- (18:16) Getting Started with Data & AI (Even If You’re Not a Data Scientist)
- (21:25) LLMs vs Classic Machine Learning: Picking the Right Approach
- (25:07) AI as a Smart Coworker: Jobs, Skills & “Vibe Coding”
- (31:25) Everyday AI, Marketing Automation & New Entrepreneurs
- (43:57) Tradeoffs: Learning Deep Skills vs Letting AI Do the Work
- (46:46) Final Takeaways & Where to Find Shannon
38 episodes
