Home

Managing Data Science Teams

How to manage data science projects and lead a data science team

This is possibly the only site dedicated to data science and analytics project management.

It explores a range of topics like the data science project cycle and workflow frameworks, what is agile data science, and how to lead a machine learning team.

So on your journey to delivering data science outcomes, explore data science project management approaches, dive into specific topics in the blog, and get certified through the Data Science Process Alliance.

Lead Data Science Teams and Processes

data science team

Lead Teams

Leading data science teams has its unique challenges – and rewards

data science process

Manage Processes

Discover various process alternatives and choose what works best for you.

data science project management training

Get Training

Learn to confidently lead data science teams and deliver outcomes.

Explore Methodologies

Like most issues in data science itself, there is no straight-forward solution to managing projects. But here’s a starting set of frameworks you could use.

managing data science with scrum

Scrum

Software engineering’s most popular agile approach has a lot going for it, but it’s rigid time-boxing creates issues for data science.

managing data science with kanban

Kanban

Its flexibility is ideal for many data science teams, especially when combined with more comprehensive project management methodologies.

managing data science projects with waterfall

Waterfall

The traditional classic project management approach doesn’t serve much purpose for data science…yet, teams – sometimes unknowingly – still use it.

Microsoft Team Data Science Process

Microsoft TDSP

Microsoft’s Team Data Science Process combines elements of CRISP-DM with modern agile software practices.

crisp dm

CRISP-DM

The classic and most popular data mining process is a good starting point but should be augmented with team-based approaches.

data driven scrum

Data Driven Scrum

A new agile framework specific for data science. Combines elements of Kanban and Scrum.

managing data science projects with the research and development life cycle

Research & Development

Some teams feel that R&D is a better fit for data science than software engineering approaches. Particularly helpful for mature teams.

domino data science life cycle

Domino Data Science Lifecycle

Domino takes the best practices from agile concepts, CRISP-DM, and 20 successful teams to create a modern lifecycle dedicated to data science.

Training and Certification

Given the requests that we’ve had for training, we’ve launched the Data Science Process Alliance.

Data Science Process Alliance

Combining data science process research with industry-leading agile training, the Data Science Process Alliance is the leading data science process membership, training and certification organization.

Download the course brochure or explore the Team Lead training, which empowers you to confidently lead data science projects.

Confidently Lead Projects

The Data Science Team Lead™ (DSTL) course provides in-depth, comprehensive, and actionable training to empower you to confidently lead data science projects.