Mar 25 • 1HR 27M

Episode 87: Product Experimentation, ML Platforms, and Metrics Store with Nick Handel

Open in playerListen on);
Datacast follows the narrative journey of data practitioners and researchers to unpack the career lessons they learned along the way. James Le hosts the show.
Episode details

Show Notes

  • (01:51) Nick shared his formative experiences of her childhood — moving between different schools, becoming interested in Math, and graduating from UCLA at the age of 19.

  • (05:45) Nick recalled working as a quant analyst focused on emerging market debt at BlackRock.

  • (09:57) Nick went over his decision to join Airbnb as a data scientist on their growth team in 2014.

  • (12:17) Nick discussed how data science could be used to drive community growth on the Airbnb platform.

  • (16:35) Nick led the data architecture design and experimentation platform for Airbnb Trips, one of Airbnb’s biggest product launches in 2016.

  • (20:40) Nick provided insights on attributes of exceptional data science talent, given his time interviewing hundreds of candidates to build a data science team from 20 to 85+.

  • (23:50) Nick went over his process of leveling up his product management skillset — leading Airbnb’s Machine Learning teams and growing the data organization significantly.

  • (26:56) Nick emphasized the importance of flexibility in his work routine.

  • (29:27) Nick unpacked the technical and organizational challenges of designing and fostering the adoption of Bighead, Airbnb’s internal framework-agnostic, end-to-end platform for machine learning.

  • (34:54) Nick recalled his decision to leave Airbnb and become the Head of Data at Branch, which delivers world-class financial services to the mobile generation.

  • (37:24) Nick unpacked key takeaways from his Bay Area AI meetup in 2019 called “ML Infrastructure at an Early Stage Startup” related to his work at Branch.

  • (40:55) Nick discussed his decision to pursue a startup idea in the analytics space rather than the ML space.

  • (43:36) Nick shared the founding story of Transform, whose mission is to make data accessible by way of a metrics store.

  • (49:54) Nick walked through the four key capabilities of a metrics store: semantics, performance, governance, and interfaces + introduced Metrics Framework (Transform’s capability to create company-wide alignment around key metrics that scale with an organization through a unified framework).

  • (55:58) Nick unpacked Metrics Catalog — Transform’s capability to eliminate repetitive tasks by giving everyone a single place to collaborate, annotate data charts, and view personalized data feeds.

  • (59:57) Nick dissected Metrics API — Transform’s capability to generate a set of APIs to integrate metrics into any other enterprise tools for enriched data, dimensional modeling, and increased flexibility.

  • (01:02:41) Nick explained how metrics store fit into a modern data analytics stack

  • (01:05:57) Nick shared valuable hiring lessons finding talents who fit with Transform’s cultural values.

  • (01:12:27) Nick shared the hurdles his team has to go through while finding early design partners for Transform.

  • (01:15:38) Nick shared upcoming go-to-market initiatives that he’s most excited about for Transform.

  • (01:17:46) Nick shared fundraising advice for founders currently seeking the right investors for their startups.

  • (01:20:45) Closing segment.

Nick’s Contact Info

Transform's Resources

Mentioned Content

Articles + Talks




My conversation with Nick was recorded back in July 2021. Since then, many things have happened at Transform. I’d recommend:

About the show

Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing

Subscribe by searching for Datacast wherever you get podcasts or click one of the links below:

If you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.