This year I captained the data science track for Boulder Startup Week (along with my partner in crime Sara Bates). Overall it was lots of work, but so rewarding to contribute to this amazing 5 days of 200+ events that are completely free and open to the public.


The events

We had a few goals for this track:

  • We wanted to organize a wide variety of events that would be interesting to both beginners thinking of getting into data science, as well as experts who want to get as technical as possible.
  • We also wanted to touch topics that were data science adjacent, but were not being represented in other BSW tracks.
  • We also wanted huge attendance numbers, diverse speakers, and a fun vibe. Duh.

Here is what we came up with.

Deep Learning Deep Dives

This event was targeted at those already familiar with AI/ML, who want to hear about advances in deep learning from the front lines.

With three talks in an hour, it was difficult for the speakers to go into technical detail, but somehow they did manage to nicely balance a discussion of specifics with perspective about where AI is going.

How to Become a Data Scientist

We wanted to have an accessible event for people curious about what data science is all about, or those transitioning into the field.

This panel ended up covering a really wide range of topics, and featured many perspectives. I really appreciated Peemin’s perspective about re-entering the workforce after time away to have kids, and all of the work she did to get into data science from an engineering background.

Key Metrics for Startups: What to Measure and Why

This would normally belong in a product track, but since that didn’t exist, we thought it important to discuss which metrics startups should be tracking, and how they should think about all these numbers.

Analyze Boulder

I’m a former co-organizer of this fantastic meetup, which features 3 5-minute lightning talks each month.

We hosted the BSW edition, which featured some fantastic talks, including a hilarious one by Janelle Shane of

Data Science Un-Event

This was an experimental event to see what happened without an agenda. People walked in, wrote topics on the white board, and we divided people into groups to discuss.

Verdict: would do it again, but we might replace with a happy hour next year :)

Data Engineering & Strategy

Data science and data engineering have a very intimate relationship, so we made sure to feature speakers who talked about data pipelines and how startups should think about their data architecture.

And more

Besides these events, we also helped out with Big Data in a Satellite’s World (best event title ever?) as well as Future Forward A.I. Learnings & Insights in Healthcare. Phew!

Take aways

We had ~300 attendees across those 6 events, and wonderful feedback. Next year I’d like this track to get more technical, perhaps with a workshop, and also more fun, perhaps with a dance party.

We missed on having an event on data ethics, an area that deserves way more attention than it gets. So that’ll be on the docket for next year.

Interested in speaking? Give me a shout!