Lead Analytic Scientist

Responsibilities

• Work with large amounts of real-world data to ensure quality through collection, normalization, and transformation.
• Research and select appropriate statistical methods and computational algorithms for predictive modeling.
• Build and oversee the development of high-end analytic models using statistical modeling techniques.
• Manage projects under time constraints and collaborate with cross-functional teams to enable integration and deployment.
• Perform production data validations and analyze models in production to assist with successful go-lives.
• Support client meetings by investigating model behaviors and providing technical expertise during pre-sales or post-implementation.

Requirements

• MS or PhD in Computer Science, Engineering, Physics, Statistics, Mathematics, or a related natural science field.
• Significant hands-on experience in predictive modeling and data mining.
• Proven ability to lead cross-functional teams on medium to large-scale projects.
• Strong scripting experience using Perl, Bash, or similar tools.
• Proficiency in at least two of the following: Java, Python, C++, or C.
• Demonstrable experience with at least three of the following: neural networks, logistic regression, non-linear regression, random forests, decision trees, support vector machines, or linear/non-linear optimization.

Preferred Qualifications

• Prior experience working with real-time payment transactional data.
• Understanding of data field availability, timing, and format requirements for downstream analytics.

Benefits

• Highly competitive compensation and rewards programs.
• An inclusive, people-first work environment with a focus on work/life balance.
• Opportunities for professional development and continuous learning.
• Access to employee resource groups and social events.

About the Company

FICO is a leading global analytics software company that helps businesses in over 100 countries make better decisions. As the creator of the iconic FICO® Score, we empower organizations through applied intelligence, machine learning, and advanced analytics to transform complex data into actionable decisions.