Team

How to Lead Data Science Teams

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leading data science teams

It’s an understatement that great leadership is challenging and rare. And leading data science teams has unique challenges: Stakeholders might get disillusioned by your team’s inability to deliver magic The battle to recruit and retain data science talent is fierce Data science’s ethical dilemmas are particularly perplexing There is not an agreed-upon process for managing […]

Team

CRISP-DM for Data Science Teams: 5 Actions to Consider

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While there is no standard process for a team to use when working on a data science project, CRISP-DM (CRoss-Industry Standard Process for Data Mining) is one framework that is often considered for data science projects. Perhaps because of this, there are lots of web sites describing the 6 phases of a CRISP-DM project, and […]

Team

10 Reasons You Need a Data Science Product Manager

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Data Science Product Manager

Unlike more tactical roles like the project manager who oversees the project life cycle or a process master who drives effective processes, the product manager is more strategic. Wearing many different hats, this product person researches market needs, defines how to map the solution to the problem space, and sets the product vision. Evolving from […]

Team

8 Key Data Science Team Roles

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Based on my personal experience, below are the 8 key data science team roles to think about when building and leading a data science team. These are not in any specific order, as their importance might vary from one project to another, or from one organization to another. Furthermore, not all roles are required to […]

Team

Data Science Team Structure

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Centralized vs Decentralized Teams

Should you have a centralized data science team or several decentralized teams? There are numerous options for a data science team structure in mid- to large-sized organizations. Yet, many organizations struggle to decide among having: A single centralized data science team (also known as “data science center of excellence” or as an “enterprise” or “shared […]

Agile

5 Agile Data Science Myths

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Agile data science myths

One of the most common questions of data science project management is some variation of: “Is agile a fit for data science?” Unfortunately – like a lot of questions in data science – this question itself is often misunderstood. Many (if not most) blog posts, on-line forums, and conversations debate this question by evaluating specific […]