Analytic Science-Scientist I

About the job

The Opportunity "You will be an integral part of a team of scientists working 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." Sr. Manager Analytic Science What Youll Contribute

• 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 projects under time and resource constraints, work with other teams within FICO (software, IT, product management, and product support) provide high quality support to enable integration and deployment of analytics software and solutions.
• May participate in post-implementation support.

What Were Seeking

• BS or MS degree in a statistics, engineering, mathematics, computer science, physics, operations research field.
• Some related experience (school or industry) in predictive modeling and data mining is preferred.
• 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 some of the following: Bayesian networks, PCA, independent component analysis, linear and logistic regressions, inference, estimation, experimental design, neural networks, SVM.

Our Offer to You

• An inclusive culture strongly reflecting our core values: Act Like an Owner, Delight Our Customers and Earn the Respect of Others.