FICO is a leading global analytics software company that helps businesses make better decisions. The Scientist I in Analytic Science will participate in compliance analytic work, developing and evaluating predictive models to solve business problems using data mining and predictive modeling techniques.
Designs and develop state-of-the-art, data-driven exploratory analysis as well as predictive and decision models to solve business problems.
Build and evaluate predictive 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, pattern identification and variable creation, selection of sampling criteria and performance definition, and variable selection.
Participate in high impact projects pertaining to predictive model development and compliance analytics.
Experiment with different types of algorithms and models, analyzing performance to identify the best algorithms to employ.
Assist with technical product support for new or existing products/services; this includes, but is not limited to, compliance-related analyses, production of sales collateral or ad-hoc investigations initiated by internal or external clients.
May participate in pre-sales support and/or provide post-implementation support.
May deliver formal presentations of work to clients as well as key internal stakeholders.
Qualification
Required
Bachelor's degree in Applied Mathematics, Statistics, Operations Research, Engineering, Computer Science or related technical discipline. Course work in probability, statistics and quantitative methods required.
Experience with one or more of R, Python, SAS, SQL, and Java/C++, experience with tools for machine learning and unstructured data analysis (e.g., H2O, Splunk, TensorFlow, etc.) 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.
Thrives in a dynamic environment and embraces continuous learning opportunities.
Preferred
Hands on related experience (academic or industry gained) in predictive modeling and data mining (Highly Preferred).
Experience with distributed computing environments (e.g., Spark, Hadoop) and cloud-based environments and services (e.g., AWS) would be a plus.
Prefer knowledge in some of the following: clustering, classification and regression trees, random forest and gradient boosting algorithms, time series analysis, Bayesian networks, PCA, independent component analysis, linear and logistic regressions, inference, estimation, experimental design, neural networks, SVM.
Benefit
Highly competitive compensation, benefits and rewards programs that encourage you to bring your best every day and be recognized for doing so.
An engaging, people-first work environment offering work/life balance, employee resource groups, and social events to promote interaction and camaraderie.
Fair Isaac Corporation enables businesses to automate, improve, and connect decisions to enhance business performance. It is a sub-organization of FICO.
