The Red Alpha data science practice grew out of Red Alpha's reputation in software and system engineering with the Department of Defense. As sometimes happens, customers who trusted our expertise in adjacent areas asked us to assist with some of their burgeoning data science problems. Culturally, it probably suffices to say that we take our work seriously but not ourselves. Our leaders have spent time in the trenches and have cursed daylight savings time changes and trailing white space more times than they can count.
We get a lot of positive feedback on our apprenticeship model, and with good reason: using data to solve business problems takes a lot of finesse both from a technical and interpersonal perspective. Our approach starts by hiring data scientists right out of undergraduate or graduate school and pairing them immediately with a senior data scientist who is held accountable for their development. For about three years, our junior data scientists spend about 80% of their time doing client work and 20% of their time on training and special projects, all along learning from (and sometimes teaching!) their more experienced colleagues. This investment in our data scientists is a boon to our clients, who, much like with Red Alpha's software and system engineering talent, get a higher degree of efficacy from Red Alpha data scientists than they are used to receiving elsewhere.