“ As a leader on our team, you will be an integral part of a team of scientists working closely with external clients to build efficient predictive models, analyze and validate production model behavior and ensure optimal model performance. There will be opportunities to support the internal technology team in development of models and get involved in sales activities related to the evaluation of models for different client environments. You may also be involved in more strategic initiatives within the department and higher level management of key projects. ” – Hiring Manager
- Build and evaluate predictive and decision models to be deployed in production systems, or for research. This includes the analysis of large amounts of historical data, determining suitability for modeling, data clean-up and filtering, pattern identification and variable creation, selection of sampling criteria, generating performance definitions and variables, performing experiments with different types of algorithms and models and analyzing performance to identify the best algorithms to employ.
- Assist with model go-lives by performing production data validations and score distribution analysis of models in production.
- Assist with client meetings to investigate and resolve production data problems. Apply data mining methodology in thorough analysis of model behavior and provide support for customer meetings, model construction and pre sales.
- Manage medium to large scope projects under time and resource constraints and work with other teams within FICO (software, IT, product management, and product support) to enable integration and deployment of analytics software and solutions.
- May participate in post-implementation and model maintenance support.
- Mentor and assist in developing growth opportunities for professional scientists.
- MS or PhD degree in a statistics, engineering, mathematics, computer science, physics, operations research field.
- Significant hands-on related experience in predictive modeling and data mining.
- Demonstrated ability to lead cross functional teams on medium to large scope projects.
Experience with Perl/Python, C, C++, or Java and familiarity with basic software design principles and coding standards and best practices.
Experience analyzing large datasets and applying data-cleaning techniques along with performing statistical analyses leading to the understanding of the structure of datasets.
Prefer knowledge of several of the following: Bayesian networks, PCA, independent component analysis, linear and logistic regressions, inference, estimation, experimental design, neural networks, SVM.
High performance culture promoting recognition, rewards and professional development.
Competitive base salary coupled with an attractive role-specific incentive plan.
Comprehensive benefits program.
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