How do you ensure a smooth hand-off between data science and engineering on ML projects? This question was originally answered on Quora by Lili Jiang.

DataOps (data operations) brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and skills to enable the data-driven enterprise.

The scientists believe that version control for cell engineering will make engineering biology more open, reproducible, easier to trace and share, and more trustworthy.

I’ve seen models take months to get to production because the data scientists and data engineers were working at cross purposes.

Eppendorf SE, a leading life science company, and DataHow AG, a pioneer in advanced data analytics and AI-driven prediction software, are excited to announce a strategic collaboration aimed at ...

But doing so requires a real push from leadership to facilitate their growth and open collaboration with all teams across the organization. Want to learn more about industrial data scientists?

With AI systems becoming easier to use and more accessible, are data scientists still key to making AI systems work for most organizations?

From big data engineers to engineers to desktop support, here’s what to look for (and what to offer) when hiring for the 10 most in-demand IT jobs for 2025.

Anaconda and HP deepen their relationship through an integration on Z by HP for Data Science products, where Anaconda is preloaded in the software stackAUSTIN, Texas, April 28, 2021 (GLOBE ...