Vectice White Papers

We build focused content around data science leadership in collaboration with our community. Our white papers are designed to provide executives and leaders with the insights they need to make better decisions and build successful data science teams.
From our panel session at ELC Annual

The Impact of
Future AI Regulation

Discover the impact of future AI Regulation from the leaders at Adobe, RingCentral, and US Bank.
Get all the key insights
Vectice White Paper

The 7 Biggest Mistakes When Documenting AI/ML Projects

Get the inside tips you need to make project documentation easy. From documenting as you go to linking key assets for easy access, we'll guide you through ML documentation best practices.
Read the easy guide to documentation success
Vectice White Paper

The EU AI Act

The EU AI Act mandates model documentation. Learn strategies and tools to achieve compliance in new white paper.
Learn what the new Act means for businesses in EU
Vectice White Paper

Evaluating Data Science Infrastructure During M&A Deals

Colleen Qiu, the Head of Data at Lindenlab, shares her extensive expertise in this must-read white paper.

As businesses increasingly recognize the value of data and AI, evaluating a company's data infrastructure has become a pivotal aspect of any successful M&A strategy.
Get all the insights
Model Risk Management Cover
Vectice White Paper

Model Risk Management

Model Risk Management (MRM) poses significant challenges due to the complexity of models, dynamic business environments, and increasing regulatory requirements. 
Learn how to tackle MRM challenges
Vectice Event

SCALE: SF Data Science Leaders

SCALE: SF Data Science Leaders event for data science leaders took in San Francisco at our headquarters.

Two amazing guest speakers from Clario and Strava came to share their expertise on topics such as:

• Getting C-suite buy-in
• Building diverse teams
• Leading remote teams in AI
• Collaboration with domain experts
Get all the insights
SCALE SF Data Science Leaders
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From the Data Science leader at Tesla, Albertsons and Metromile

Deliver AI Faster With The [2x3] Methodology

Developed by Colleen Qiu, former Head of Data Science at Tesla, the 2x3 Methodology is a three-stage approach to help data science teams deliver AI solutions faster.

The approach reduces the time required to deliver AI projects and ensures that data science teams are aligned with the organization’s objectives.
Access Now
From an industry veteran

How Data Science Entered the Corporate World

Jon Shepherd, advisor at Vectice, shares insights on the early days of data science. Companies profited from the demand for data, and an academic branch of analysis came to dominate in finance and business.

Learn how data science evolved from a niche domain to a trendy field.
Learn how it all started
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Vectice Event

THRIVE: NYC Data Leaders

From our event, Thrive: NYC Data Leaders, more than 40 data science leaders from various industries and three guest speakers came to our event to discuss essential topics when leading AI teams.

The speakers shared great insights on the following:

• Aligning data science with the rest of the business
• Hiring and retaining data talent
• Centralized vs. embedded teams
Get their key insights
Vectice Event

Voices of ML Leaders

At our Voices of ML Leaders event, more than 25 Vice Presidents and Directors from the top companies in various industries joined us at our headquarters to discuss important topics related to leading AI teams.

Our guest speakers included AI leaders from Microsoft, Kohl's, and Yelp.

Topics discussed included:
• Talent acquisition & retention
• Aligning AI with the rest of the business
Get their key insights
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Vectice Introduces Auto-Documentation Solution for ML Projects & Their Governance

Join the Vectice Community of 1,250+ AI Leaders