  A common expectation is that career productivity peaks rather early and then
gradually declines with seniority. But whether this holds true is still an open
question. Here we investigate the productivity trajectories of almost 8,500
scientists from over fifty disciplines using methods from time series analysis,
dimensionality reduction, and network science, showing that there exist six
universal productivity patterns in research. Based on clusters of productivity
trajectories and network representations where researchers with similar
productivity patterns are connected, we identify constant, u-shaped,
decreasing, periodic-like, increasing, and canonical productivity patterns,
with the latter two describing almost three-fourths of researchers. In fact, we
find that canonical curves are the most prevalent, but contrary to
expectations, productivity peaks occur much more frequently around mid-career
rather than early. These results outline the boundaries of possible career
paths in science and caution against the adoption of stereotypes in tenure and
funding decisions.
