Lead Analytic Scientist

MS or PhD degree in computer science, engineering, physics, statistics, mathematics, operations research or natural science fields with significant years of hands-on related experience in predictive modeling and data mining.
Experience analyzing large data sets and applying data-cleaning techniques along with performing statistical analyses leading to the understanding of the structure of data sets.
Proven ability to lead cross functional teams on medium to large scale projects and handling client interactions requiring strong communication skills.
Strong scripting experience using Perl, Bash, or similar.
Experience working with two of the following: JVM Languages (Kotlin, Scala, Java), Python, C++ or C.
Proven and demonstrable experience with at least three of the following: neural networks, logistic regression, non-linear regression, random forests, decision trees, support vector machines, linear/non-linear optimization.
Proficiency with APIs (Spark API, PyTorch) and Conda or virtual environments.
Familiarity with Docker and Gradle.
AWS experience is a plus.

Work with large amounts of real-world data and ensure data quality throughout all stages of acquisition and processing, including data collection, normalization and transformation.
Research and select appropriate statistical methods and computational algorithms.
Build and/or oversee teams building high-end analytic models for relevant problems using statistical modeling techniques. Manage these projects under time constraints, working with other teams within FICO to provide high quality support to enable integration and deployment of analytics software and solutions.
Assist with model go-lives by performing production data validations and analysis of models in production.
Assist with client meetings to investigate and resolve problems. Apply data mining methodology in thorough analyses of model behaviors and provide support for customer meetings, model construction and pre-sales. May also participate in post-implementation support.