Question: What occupation did Maxim Kontsevich and Andrey Kolmogorov both share?
Context: In the mathematical theory of knots, the Kontsevich invariant, also known as the Kontsevich integral of an oriented framed link, is a universal Vassiliev invariant in the sense that any coefficient of the Kontsevich invariant is of a finite type, and conversely any finite type invariant can be presented as a linear combination of such coefficients.  It was defined by Maxim Kontsevich. In probability theory, Kolmogorov's Three-Series Theorem, named after Andrey Kolmogorov, gives a criterion for the almost sure convergence of an infinite series of random variables in terms of the convergence of three different series involving properties of their probability distributions. Kolmogorov's three-series theorem, combined with Kronecker's lemma, can be used to give a relatively easy proof of the Strong Law of Large Numbers. Maxim Lvovich Kontsevich (Russian: Макси́м Льво́вич Конце́вич ;   ; born 25 August 1964) is a Russian and French mathematician.  He is a professor at the Institut des Hautes Études Scientifiques and a distinguished professor at the University of Miami.  He received the Henri Poincaré Prize in 1997, the Fields Medal in 1998, the Crafoord Prize in 2008, the Shaw Prize and Fundamental Physics Prize in 2012, and the Breakthrough Prize in Mathematics in 2014. In mathematics, the Kontsevich quantization formula describes how to construct a generalized ★-product operator algebra from a given arbitrary Poisson manifold.  This operator algebra amounts to the deformation quantization of the corresponding Poisson algebra.  It is due to Maxim Kontsevich. In mathematics, the Landau–Kolmogorov inequality, named after Edmund Landau and Andrey Kolmogorov, is the following family of interpolation inequalities between different derivatives of a function "f" defined on a subset "T" of the real numbers: In mathematics, Fisher's equation (named after statistician and biologist Ronald Fisher; also known as Kolmogorov–Petrovsky–Piskunov equation—named after Andrey Kolmogorov, Ivan Petrovsky, and N. Piskunov—or KPP equation or Fisher–KPP equation) is the partial differential equation: In statistics, originally in geostatistics, kriging or Gaussian process regression is a method of interpolation for which the interpolated values are modeled by a Gaussian process governed by prior covariances, as opposed to a piecewise-polynomial spline chosen to optimize smoothness of the fitted values.  Under suitable assumptions on the priors, kriging gives the best linear unbiased prediction of the intermediate values.  Interpolating methods based on other criteria such as smoothness need not yield the most likely intermediate values.  The method is widely used in the domain of spatial analysis and computer experiments.  The technique is also known as Wiener–Kolmogorov prediction, after Norbert Wiener and Andrey Kolmogorov. Andrey Nikolaevich Kolmogorov (Russian: Андрей Николаевич Колмогоров ; ] , 25 April 1903 – 20 October 1987) was a 20th-century Soviet mathematician who made significant contributions to the mathematics of probability theory, topology, intuitionistic logic, turbulence, classical mechanics, algorithmic information theory and computational complexity. In Kolmogorov's probability theory, the probability "P" of some event "E", denoted formula_1, is usually defined such that "P" satisfies the Kolmogorov axioms, named after the Russian mathematician Andrey Kolmogorov, which are described below. The Kolmogorov backward equation (KBE) (diffusion) and its adjoint sometimes known as the Kolmogorov forward equation (diffusion) are partial differential equations (PDE) that arise in the theory of continuous-time continuous-state Markov processes.  Both were published by Andrey Kolmogorov in 1931.  Later it was realized that the forward equation was already known to physicists under the name Fokker–Planck equation; the KBE on the other hand was new.
Answer: mathematician