To learn all about Data Science Products and the role they play in product management, you should watch the whole video from Justin Norman’s Speaker Series in San Francisco. The highlights are detailed below.

Product Data Science means building data products, tools and measurement strategies that impact the consumer using a rigorous statistical methodology, expertise, and experience.

Just like products have a product lifecycle, a DS product has its own product lifecycle.

Here is the Data Science (DS) Product Lifecycle:

  1. Ideation and Design
  2. Data Exploration and Pipeline Development
  3. Product Development
  4. Experimentation
  5. Release!

Types of DS Products:

  • Application embedded: Some kind of applied (usually probabilistic) data science or Machine Learning built into an application as a feature. Ideally, without user knowledge.
  • Actionable research: It’s not a feature. It’s not something that’s going into the application directly. It’s metrics to help make decisions on where time and resources should be spent.
  • Experiment design: Have an experiment plan to help guide the conversation between Data Scientists and Product Managers about the measurement strategy. The Data Scientists, Engineers, and PMs must partner during the experiment execution. Your plan must keep up with the changes in thinking that come as a product evolves.
  • Reusable analysis tools: Reusable code and tools enable and promote the use of data in product development. Data Science helps Product Managers explore and select which metrics to use.
  • Confident monitoring: When you release a product that has some kind of treatment from a statistical perspective in it, you can pretty much guarantee that you’re gonna have to redo it soon. So, if you have monitoring in place you’re able to react to that quickly. 
  • External reporting: These DS products promote the brand and engage the community outside of the core product.

The DS Product Manager Toolbox

  • Data Lifecycle and Pipeline Management
  • Experimentation and metrics
  • DS Development Process

Core Data Science PM Responsibilities:

  • Decide on core function, audience and desired use of Data Science product
  • Evaluate any inputs and ensure they’re maintained through the lifecycle
  • Orchestrate the cross-functional team (Data Engineering, Research, Applied Machine Learning, Data Science, Machine Learning Engineering, Software Engineering, Data Platform, Metrics Platform, Experimentation Platform)
  • Decide on key interfaces and designs: data features and UI/X
  • Work with Engineers and Data Scientists during development to determine the tech stack
  • Coordinate maintenance and support after the product release
About the speaker
Justin Norman Yelp, VP, Data Science Member

Justin serves as Head of Data Science at Yelp. He is a career data professional and Data Science leader with experience in multiple industries and companies. Previously, Justin was the Director of Research and Data Science at Cloudera Fast Forward Labs, head of Applied Machine Learning at Fitbit, the head of Cisco’s Enterprise Data Science Office and a Big Data Systems Engineer with Booz Allen Hamilton. In another life, Justin served as a Marine Corps Officer, with a focus in Systems Analytics and Device Intelligence. Justin is a graduate of the US Naval Academy with a degree in Computer Science and the University of Southern California with a Master’s Degree in Business Administration and Business Analytics.

About the host
Oren Root VMware, Director, Product Management, - VMware Cloud on AWS

Oren is a Product leader with over a decade of experience in challenging the status quo at large companies as well as start-ups.

Provide your rating for this post
If you liked this post, please use the buttons to the left to share it with a friend or post it on social media. Thank you!

Leave a Reply

Read more

Embedded Analytics Series – Data Monetisation at ICIS

Continuing the Embedded Data Analytics Series from Tableau, dive into a roundtable on Data Monetisation with a panel of domain experts and thought leaders.

Datasite CPO on Making Winning Products

Thomas Fredell recently spoke at Favor Delivery/H-E-B Eastside Tech Hub in Austin to help PMs understand how to build winning products.

HomeAway fmr Engineering VP on Data-Driven Product Management

HomeAway fmr VP of Engineering, Jon Loyens, joins Products That Count to explain the ins and outs of data-driven product management.

/ Register for Free

Don’t be left behind in your career. Join a growing community of over 500K Product professionals committed to building great products. Register for FREE today and get access to :

  • All eBooks
  • All Infographics
  • Product Award resources
  • Search for other members

Coming soon for members only: personalized content, engagement, and networking.