Scientific Software Engineer - C/C++, Mathematical, Algorithms, Eigen, SQL, Big Data
AgreeYa is an IT Solutions and Services company founded in 1999 by ex-Deloitte talent and has managed 400% revenue growth in the last five years due to strong strategic relationships. We fly beneath the radar, a little, and like it that way. AgreeYa is headquartered in Folsom, CA with 22 offices in eight countries. We are CMMI level 5 and ISO 9001:2008 certified with a delivery and SLA framework backed by proven best practices and full management commitment. One of our valued clients has engaged us to locate (2) two Senior Software Engineers to get heavily involved in design, coding, testing, and support of a cutting edge data cleansing, demand modeling, forecasting, and optimization platform. This individual must possess expert-level software engineering skills and practices. The successful candidate will have deep experience designing and implementing high-performance computing applications in team-based software development organizations. This predictive technology accounts for price, promotion, and markdown activities enabling a coherent view of customer demand and applies an advanced proprietary approach to analytics and science to predict customer behavior. The Software Engineer will work with Product Management to understand and refine business requirements, will design solutions to meet business requirements, engage directly in performance tuning and optimization, work with scientists to develop and deploy scalable scientific algorithms, coordinate designs and interfaces with other development organizations (database engineering, web development), collaborate with Knowledge Management to create documentation for user guides, online documentation, and release notes, and engage with QA and Client Services to support testing, configuration, and bug fix activities. Key Responsibilities: -Design, code, test, and support production software for high-quality, repeatable, and automated data cleansing, modeling, forecasting, and optimization -Design and implement software in a relational database as well as in a high-level programming language. -Create standardized processes to design, code, test, and support high-quality production software for implementing scientific algorithms -Create and implement mathematical models and scientific algorithms including the development of robust, rapid, and efficient numerical algorithms -Execution of proof-of-concept pilots and implementation support -Knowledge transfer throughout the organization, internal presentations, and white papers establishing thought leadership and capability excellence within the platform Requirements: -Bachelor’s degree in Mathematics, Engineering, Computer Science, or Physical Sciences -Expert-level proficiency in an object-oriented language such as C++, Java, or C# -RDBMS proficiency and ability to write SQL queries (SQL Server / T-SQL, Oracle PL-SQL, etc.) -Experience with high-performance applications and software performance optimization -Experience in team-based lifecycle software development -Firm grasp of statistical analysis principles -Excellent teamwork and communications skills Optional Skills that would add value include: -Experience with .NET 4.0 framework strongly desired -MS Visual Studio IDE -N-Unit, J-Unit, or similar unit test framework, test-driven development methodologies - Microsoft SQL Server / T-SQL -“Big Data” – experience with non-relational / NoSQL highly-scalable data repository platforms (MongoDB, Hadoop, Cassandra, etc.) -High-performance / supercomputing / parallel processing / grid computing experience -Monte Carlo methods or other simulation & testing techniques -Hierarchical and non-hierarchical clustering techniques (K-means, agglomerative clustering, divisive clustering, graph theory, QT clustering) -Factor analysis, sensitivity analysis, Fourier / spectral analysis, eigen systems analysis, Principal Components Analysis (PCA) -Optimization techniques (linear programming, integer programming, SQP, gradient methods) -Genetic algorithms simulated annealing, neural networks, machine learning -Decision theory, discrete choice models, propensity modeling, choice models -Statistical analysis, optimization and data visualization packages/platforms such as Matlab, SAS, SPSS, R, CPLEX, AIMMS, or KNITRO -Domain expertise in price optimization, demand forecasting, or inventory optimization -Retail or Supply Chain industry experience
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