The problem is that the derivative at 1 is small enough to be considered zero (according to the AccuracyGoal):

f'[1]
(*  -2.26383*10^-9  *)

Pick an AccuracyGoal several orders of magnitude above 9:

FindMinimum[f[x], x, AccuracyGoal -> 16]
(*  {0.0024294, {x -> 160.}}  *)

There is a FindMinimum::lstol warning because at x -> 160., the interpolating function is not differentiable.

If the singularity or the warning troubles you, consider a method that does not use derivatives:

FindMinimum[f[x], x, Method -> "PrincipalAxis", AccuracyGoal -> 16]
(*  {0.0024294, {x -> 160.035}}  *)

Alternatively, one might use the "Spline" method of interpolation:

Clear[f];
f = Interpolation[d, Method -> "Spline"];
FindMinimum[f[x], x, AccuracyGoal -> 16]
(*  {0.00242939, {x -> 160.498}}  *)

Of course, with the error inherent in interpolation, any of the answers is probably sufficiently accurate (or if not sufficient, then as accurate as is possible).