We’re certainly not the first people to have these realizations, but we think our approach sets us apart.

It you’ve got a data science opportunity that fits the description above, off-the- shelf solutions probably don’t exist yet .Depending on your problem and how common it is, they may never exist. We believe that the way to improve people, organizatons, and even society is by tailoring an approach to the specific needs, culture, and goals of the problem at hand.

A data science team must be able to imagine a wide array or potential solutions and continually make decisions about which ones to pursue and which ones to throw out. That’s why, for us, building a heterogeneous team is as much a pragmatic decision as anything else; research has shown that diverse teams consistently outperform homogeneous ones at creative tasks and decision making.

We recognize that from the outset we often don’t know exactly what problem to solve, and that in the process of solving it the problem will change. Without willingness to periodically consider ourselves ignorant, reflect on the problem, and adapt by building something new, it’s easy to struggle with deciding what to solve, or worse, blindly sink time and resources into things that don’t matter.

We believe in the fundamental principle of scientific inquiry. Scientists are encouraged to be skeptical of their own hypotheses and to subject them to rigorous testing and peer review.

Data science results can be complex and nuanced, but it should not require data science skills to understand them. We believe it is always the responsibility of the data scientist to communicate results and design tools in ways that are meaningful to others.