Working at Domino Data Lab | Glassdoor

Domino Data Lab Overview

San Francisco, CA
51 to 200 employees
Company - Private
Enterprise Software & Network Solutions
Unknown / Non-Applicable
The world is changing. More and more companies are building models into the core of their business. Insurance is priced based on models, cancer drugs are developed using machine learning, and predictive analytics make car manufacturer supply chains more ... Read more

Mission: Make the world run on models.

Company Updates

  • Domino is hosting Rev - a conference for Data Science Leaders. Nate Silver and Cathy O'Neil are headlining. Find out more at:

    Rev | Data Science Leaders Summit

    Rev will bring together the data science leaders and practitioners of today and tomorrow, May 30-31 in San Francisco. Attendees will learn how to weave data science into the fabric of their organizations as a core capability, making its business impact repeatable at scale.

  • Learn more about Domino through a Q&A with our CEO, Nick Elprin:

    Q&A with Domino Data Lab's CEO

    The field of data science is fairly young and evolving extremely rapidly. Finding people who can harness the tornado of big data tech is a major challenge. One of the up and coming vendors who are making data science more accessible is Domino Data Lab.

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Domino Data Lab Video

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Domino Data Lab – Why Work With Us?

One Place for Data Science Work

Develop, deploy, and collaborate — using your existing tools and languages.

Domino accelerates the development and delivery of models with key capabilities of infrastructure automation, seamless collaboration, and automated reproducibility. This greatly increases the productivity of data scientists and removes bottlenecks in the data science lifecycle.

Compute Grid & Environment Management enables more data science and less devops

  • Avoid overwhelming your local machine by leveraging scalable compute with powerful, centralized hardware — in the cloud or on premise.
  • Eliminate barriers to leveraging latest deep learning techniques with one-click access to GPU hardware.
  • Reduce software configuration time by running your code in Docker containers, configured to create shared, reusable, revisioned Compute Environments.

Collaboration Hub & Reproducibility Engine

Increase productivity and reduce risk, together

  • Reduce key-man and operational risk by automatically preserving all key project information with Domino’s containerization and dependency map– save data, software configurations, code, parameters, results, discussion, and delivered artifacts as they happen.
  • Streamline knowledgement management with all projects stored, searchable, and forkable.
  • Avoid a cold start by using native integrations with popular source control systems like GitHub.

Data Science Workbench

Faster iteration and experimentation

  • Work instantly by spinning up interactive workspaces with one click — using the tools you already know and love, e.g., Jupyter, RStudio, SAS, and Zeppelin.
  • Tackle complex problems by running, tracking, and comparing batch experiments in parallel with any language, even commercial languages like SAS or Matlab.
  • Minimize changes to your existing workflow by connecting to any data including cloud databases and distributed systems like Hadoop and Spark
  • Instantly leverage all popular tools with the our pre-packaged Domino Analytics Distribution (includes database drivers, Anaconda Python, popular deep learning packages, visualization packages, etc.) Or customize your own environment without risk of affecting other users.

Faster Delivery and manage scalable data products

  • Eliminate delays and risk from recoding of models by deploying models as batch or real-time APIs of your Python and R models.
  • Support web-scale processes with horizontal scalability.
  • Minimize delivery risk with instant rollback to old versions of models.
  • Measure ROI faster: Split traffic across versions to do A/B testing.

Deliver powerful insights to stakeholders

  • Communicate business benefits. Publish visualizations using open source data science tools, including knitr, Plotly, D3, etc. or for commercial tools like Tableau.
  • Expose complex results in business-friendly manner. Publish interactive dashboards and web apps using Shiny and Flask.
  • Remove low-value admin work. Schedule recurring tasks to update reports — serve results through the web or send to stakeholders via email.

Enterprise Identity and Access Management

  • Seamlessly manage platform as integral asset in enterprise IT stack with cost controls and governance.
  • Manage security for consuming and modifying production models.
  • Automate identity management with integrations into LDAP.
  • Manage hand-offs, sensitive information, and regulatory standards with integrated and granular user access management.

Domino is helping companies maximize the value of their quantitative research.
We’re building the platform that enables thousands of data scientists to develop better medicines, grow more productive crops, build better cars, or simply recommend the best song to play next.

Domino Data Lab Reviews

  • Featured Review

    Helpful (4)

    "Excellent culture, people, and product"

    • Work/Life Balance
    • Culture & Values
    • Career Opportunities
    • Comp & Benefits
    • Senior Management
    Current Employee - Director of Sales in San Francisco, CA
    Current Employee - Director of Sales in San Francisco, CA
    Positive Outlook
    Approves of CEO

    I have been working at Domino Data Lab full-time (Less than a year)


    Massive market potential, product that data scientists love, transparent leadership that listens to employees. Brilliant and humble CEO, and supportive VPs & Directors.


    No 401(k) match, no tuition reimbursement.

    Advice to Management

    Continue listening to your team members, stick to the core values, and we will deliver exponential growth.

See All 27 Reviews

Domino Data Lab Photos

Domino Data Lab photo of: work work work work work
Domino Data Lab photo of: Company Kickoff Party 2019
Domino Data Lab photo of: Company Kickoff Party 2019
Domino Data Lab photo of: Company Kickoff Party 2019
Domino Data Lab photo of: Company Kickoff Party 2019
Domino Data Lab photo of: Company Kickoff Party 2019
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Domino Data Lab Interviews



Getting an Interview

Getting an Interview





    QA Engineer Interview

    Anonymous Interview Candidate in San Francisco, CA
    No Offer
    Neutral Experience
    Difficult Interview


    I applied online. The process took 3 weeks. I interviewed at Domino Data Lab (San Francisco, CA) in June 2020.


    The panel had 4 (1-on-1) interviews. The technical part was really good and the interviewer was collaborative and willing to help. Learned some new function parameters I didn't know before. Another 1-on-1 revealed I need to learn/ refresh the system design.
    The most frustrating question during the whole panel was: What will you do if some tests from your test suit are failing from time to time and the developers continue to complain about it?
    That was a red flag for me. First, why do you have unreliable tests in your test suit so that other engineers have no confidence in the QA work? Second, there might be some communicating issues between QA and Dev teams at Domino.
    The overall impression: though the people seem to be really smart, their strained smiles and semi-grumpy faces indicate huge collaboration problems and tons of pressure at the company.

    Interview Questions

    • Some weird QA tasks, one technical HackerRank problem, behavioral questions, and debugging flow.   Answer Question
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Domino Data Lab Awards & Accolades

  • Inc. 5000, Inc., 2019

Pledges & Certifications

Pay Equality Pledge

Committed to paying equitably for equal work & experience

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