Data Science Project Management

Managing Data Science Teams

How do you effectively manage data science projects? 

Like most issues in data science itself, there is no straight-forward solution to managing projects. However, by arming yourself with a broader understanding of data science life cycles, as well as project management approaches that can be applied to data science teams, you’re more likely to find or develop a methodology that works. 

This is possibly the only site dedicated to data science project management. For example, it explores what is agile data science and how you could lead a data science team via an agile data science approach?

So learn why data science needs to evolve its own project management approaches, explore methodologies in the data science project management guide, and dive into specific topics in the blog.

Explore Methodologies

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 (TDSP)

Microsoft TDSP

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

crisp dm process model

CRISP-DM

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

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.

bimodal data science

Bimodal

Why not combine the best of waterfall and agile? Actual results may vary…

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

Data Science Process Alliance Team Lead

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.