Analytic Science Lead Scientist (AI)

TL;DR

Analytic Science Lead Scientist (AI): Developing and overseeing high-end analytic models for real-world financial and security problems with an accent on predictive modeling, data mining, and statistical algorithms. Focus on leading cross-functional teams, integrating AI/ML solutions into production environments, and resolving complex client-facing analytical challenges.

Location: San Diego, CA (Onsite)

Salary: $120,000–$189,000

Company

A leading global analytics software company providing industry-leading solutions in credit scoring, fraud detection, and lending to businesses in over 100 countries.

What you will do

• Work with large-scale real-world data, ensuring quality through collection, normalization, and transformation.
• Research and select advanced statistical methods and computational algorithms for complex problem solving.
• Build and oversee teams developing high-end analytic models using statistical modeling techniques.
• Manage project timelines and support the integration and deployment of analytics software.
• Perform production data validations and analyze model behaviors post-implementation.
• Assist in client meetings to investigate problems, provide support for model construction, and aid in pre-sales activities.

Requirements

• MS or PhD in computer science, engineering, physics, statistics, mathematics, or related fields.
• 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.
• Experience working with 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.

Culture & Benefits

• Inclusive work environment reflecting core values of ownership, customer focus, and mutual respect.
• Competitive compensation, benefits, and rewards programs.
• Commitment to professional development through learning experiences and career growth opportunities.
• Focus on work-life balance with employee resource groups and social events.