risk

CTO - Economic Risk Management (ERM)
San Francisco, CA - Full Time
Equity - join the founding team
3 to 4 years experience preferred
Computer Science / Physics / Applied Math / Financial Engineering - background in machine learning algorithms, distributed computing, and data mining preferred

DESCRIPTION:
CTO - Algorithms, Data Structures, Hadoop, Java, Python, R, BASH programs
Skills Required - Data mining of large data sets (Big Data!), Hadoop, Java / Python / C++, Linux, Statistics and Probability Theory

We're a San Francisco based startup that specializes in developing supply chain risk management software for the manufacturing, construction, and transportation industries.  Our founders studied at Berkeley and Stanford, and have worked at some of the leading companies in software, finance, and manufacturing, including IBM, Axioma, FTSE, Alphacet, MSCI, and Toyota.  Our advisers include David Leinweber of LBNL, and our research includes several published papers, a working prototype, and a large database of financial and economic time series.  We have two development clients - a large manufacturing company and an even larger supply chain certification firm.  Going forward, we're looking for a brilliant systems architect to build out the platform.

The ideal candidate will be a Computer Scientist who can write software to analyze terabytes of data and billions of rows to discover correlations and patterns in economic data, and to come up with algorithms and strategies for reducing customers' risk exposure. Typical candidates for this role have not only developed data mining algorithms but also built large scale systems incorporating them.

RESPONSIBILITIES:
~Research, investigate, pick industrial data mining/machine learning algorithms.
~Implement these algorithms using grid computing & affect the product direction.
~Develop and support the data store and cloud compute cluster

EXPERIENCE:
1.) Experience in data mining and machine learning on large amounts of sparse data. Must have a good understanding of algorithms, data structures, performance optimization techniques, and object-oriented programming. Large scale data manipulation.
2.) BS/MS in Computer Science / Physics / Applied Math / Financial Engineering (with emphasis in data mining/machine learning/artificial intelligence/mathematics/OR).
3.) Experience developing software using Java / Python / C++ / R on Linux. Experience with Hadoop or MapReduce is a huge plus!
4.) Should have a strong background in Linear algebra/Matrix operations.

Other strong pluses and areas of interest include:
~Machine learning algorithms (neural networks, support vector machines, bayes, genetic algorithms)
~Grid Computing/Parallel Computing/Distributed Computing
~Time series analysis (GARCH, ARMA, etc.)
~Statistical analysis (regression, correlation)
~Experience with Monte Carlo simulation