Mitchell Zukor is a statistician and probabilist whose area of expertise is the prediction of disasters. To many people, including the reporter/narrator, this makes him a humorous and pathetic number cruncher:
(quoted from Odds Against Tomorrow)
He flipped on his desk lamp, pounded numbers into his calculator, and scrawled equations and odds ratios. It was a nearnightly ritual. The next morning we'd find him there asleep, face down on his papers, his cheek ink stained with numbers like a prison tattoo.
None of us, to be clear, lost any sleep over Mitchell's prophecies. We thought he was a little mad, and a little depressed, even by U of C standards. He may have understood numbers, but everyday life was too complex for him.

However, especially in the fictional world of this novel where Seattle was leveled by an earthquake, these skills make him a hero in the insurance industry.
In fact, it is not so much his ability to compute the probabilities accurately as it is the extent to which he can share his own fear, his panic, with potential clients that is his most valuable asset.
He works in the Department of Equities, Assets and Derivatives and considers himself fortunate not to have been placed in "Equations and Vectors" (E and V) rather than in DEAD because
(quoted from Odds Against Tomorrow)
The guys in E and V were glorified accountants. their job was to devise algorithms and formulas to predict complex market activities and the rate of return on various investments. Even his DEAD colleagues seemed lively compared with the forsaken souls in E and V. They were the nerds of the quant world. Which was saying something.

Despite the broad farce apparent in that excerpt, the book seems somewhat serious. Perhaps it is because the author is an essayist and is attempting to get across his opinions regarding the environmental risks we face and the way the business world works. (As an example of the former, one need only look at the cover which shows the skyscrapers of Manhattan sticking up out of the water. The latter is largely personified in the character of Alec Charnoble, the head of a company called FutureWorld.)
In terms of mathematics, the author tosses around terms like "deltagamma approximations" and "Monte Carlo simulations", not really expecting the reader to know or care what they mean. Also, as you have already seen above, there are traditional "math nerd" stereotypes. However, there are also passages which convey the power and universality of mathematics.
(quoted from Odds Against Tomorrow)
There was no escaping math, after all. It was everywhere, especially in nature. You could go so far as to say that math was nature. Pi described the arc of a rainbox, the way ripples spread in a body of water, the dimensions of the moon and sun. Fractals could be observed in halved sections of red cabbage, the topography of deserts, the branching of lightning bolts. ... When all the people were gone, the numbers would persist. Always the numbers, an infinite chain running to the edge of the universe.

[While reading this book, I couldn't help but wonder whether the paranoid character of Mitchell Zukor was in any way like the author himself. That question was answered (in the affirmative) once I saw Nathaniel Rich's article in the New York Times on his refusal to be scanned at airports.]
Contributed by
RdR
I've voted "A Bit of Math", because the author mainly uses math terms (and one formula) as props, without any real substance or even explanation about how the math might work. I contrast this with, say, "Cryptonomicon" where explanation in the form of dialogue and action is given of mathematical concepts like encryption and the statistics of patterns. Also, in "Odds against tomorrow" there is only a minor amount of the sociology or psychology of doing math  mainly the usual trope of math nerd in the backroom (although the main character does eventually get to talk to people).
Overall, it was a pleasant read, and with decent character interactions and development. Still, a pity that there wasn't more of the fascinating world of disaster modelling.

