Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

Most of us reading this writeup have probably had at least one interaction with a recruiter. Most of us reading this writeup probably don’t have a deep knowledge of recruiting — what recruiters do, how they help teams scale, and what the other 90% of the iceberg you don’t see as a candidate consists of. Recruiters are on the front lines of attracting talent and making sure that a team grows the right way, and this episode we talk about how to make sure that happens. You’ll hear about all that and more, including:

Full show notes: https://medium.com/klaviyo-data-science/klaviyo-data-science-podcast-ep-12-how-data-science-teams-should-grow-d1c7005b1dc8

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

A question we frequently get asked is: what books should I read to be a better data scientist/machine learning engineer? This may not surprise you, but there isn’t just one answer — depending on the skills you have, your knowledge base, the point of your career that you’re in, and many other factors, there are many books you could read that will help you learn more. This month, we cover several ways to improve the skills you need to contribute to a data science team. You’ll hear about all that and more, including:

Some more reading or viewing that we mention in this episode:

Contact us

The best place to reach the podcast is by messaging me on Twitter: https://twitter.com/lawson_m_t.

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

This is a math-heavier episode than usual — we’re going to dive into probabilistic distributions and talk about systems of estimators. Even if that’s not your background, though, you should still find this episode useful. That discussion is all based in something crucial to real-life businesses around the world: customer lifetime value, or CLV. What exactly does CLV tell you, how exactly is it calculated and predicted, and why exactly does it matter to your business? You’ll hear about all that and more, including:

Contact me

The best place to reach the podcast is by messaging me on Twitter: https://twitter.com/lawson_m_t.

You’ve probably heard of benchmarks. You’ve probably even used them. But what exactly are benchmarks, how are they useful, and how can you go about building a system to make benchmarks in your own industry? You’ll hear about all that and more, including:

Some more reading or viewing that we mention in this episode:

Klaviyo helps growth-focused ecommerce brands drive more sales with super-targeted, highly relevant email, Facebook, and Instagram marketing. Interested? We’re always looking for great people to join our team.

The best place to reach the podcast is by messaging me on Twitter: https://twitter.com/lawson_m_t.

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

We have a bit of a different episode this month. Instead of diving deep into a specific topic, I asked 14 members of the Klaviyo data science team to give their personal highlight for 2020 as a year in data science. You’ll hear about a bunch of fascinating data science topics, including:

Full Episode Notes

See https://medium.com/klaviyo-data-science/klaviyo-data-science-podcast-ep-8-2020-a-data-science-year-in-review-88be9b534183.

Contact Me

Contact me on twitter: @lawson_m_t

This podcast was recorded in January 2021, before Abigail Thorn publicly came out as transgender. It currently refers to her by her former name, but will soon be edited. Congrats to Abigail!

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

All data science work at scale rests on a solid foundation of engineering. We discuss how to establish that foundation — from what goes into software engineering to begin with to the specifics of how to prepare for big seasonal events like Black Friday and Cyber Monday. You’ll hear from software engineers on the team about:

Full show notes available at https://medium.com/@michael-lawson-96765/klaviyo-data-science-podcast-ep-7-laying-a-stable-engineering-foundation-ba6462aa0db.

Contact us: @lawson_m_t on Twitter.

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

As the calendar changes, so do the right steps to take for your e-commerce business. We wade into the waters of seasonal changes in behavior, data, and logistics, and we take a deeper look at how to navigate them. You’ll hear from data scientists and product analytics about:

Full show notes are available at https://medium.com/@michael-lawson-96765/klaviyo-data-science-podcast-ep-6-navigating-seasonality-in-e-commerce-1bac11b8bf13.

Contact us: @lawson_m_t on Twitter.

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

Recommender systems: how do they work?

We get recommendations for all sorts of things today: routes to take when we drive, places to eat, books to read, petitions to sign, and of course, things to buy. We take a deeper look at the task of making the data science and software systems that dispense useful recommendations at scale, with a special focus on recommending ecommerce products. You’ll hear from data scientists and engineers about:

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

Data-centric teams likely take it as a given that good reporting is a key to living a happy life, but what exactly makes a report good? We dive into the topic of reporting and discuss ways to make a report exceed expectations. You’ll hear from data scientists and product designers about:

In this episode, we take a deep dive into a recent feature the team built, signup form A/B testing, to give you a taste of what it’s like to build software for data science. You’ll hear from data scientists, product designers, and software engineers. We discuss:

Questions, comments, clarifications, or concerns? Reach out to Michael Lawson!