
Scienaptic AI

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About
Scienaptic AI provides an automated credit decisioning platform powered by inclusive AI, designed to help lenders approve more applicants at lower risk. It significantly increases approvals for direct vehicle loans, automates a high percentage of portfolios, and offers a strong return on investment. The platform enhances lending processes through AI models trained on over 400 million records, offering 7X more risk differentiation than bureau-based scores. It is trusted by over 150 lenders, enabling compliance with regulations and ensuring no bias in design through disparate impact analysis. Scienaptic AI seamlessly integrates with existing Loan Origination Systems (LOS) and helps score over 95% of applications without traditional credit scores, leading to more approvals for protected classes and underserved applicants. It focuses on fair and equitable lending outcomes.
Platform
Features
• advanced machine learning algorithms
• comprehensive risk and fair lending monitoring
• fraud detection and early warning
• scoring applications without traditional credit scores
• compliance and bias analysis
• seamless los integration
• inclusive ai for enhanced lending
• automated credit decisioning
Job Opportunities
Principal Data Scientist
Scienaptic AI is a credit decisioning platform that uses inclusive AI to automate and optimize lending processes for financial institutions.
Education Requirements:
Master’s degree, or foreign degree equivalent, in Business Analytics, Statistics, Mathematics, Computer Engineering, or a related field
Experience Requirements:
4 years of experience in Machine Learning, Data Analytics, and Visualization.
4 years of experience creating Machine Learning pipelines and optimization
4 years of experience using open-source programming languages for large scale data analytics, including data handling and machine learning packages.
4 years of experience in creating machine learning models and strategies
1 year of experience in AI research and deep learning
Other Requirements:
Employer will only employ those who are legally authorized to work in the United States for this opening.
Any offer of employment is conditioned upon the successful completion of a background check and drug screen (as applicable).
Responsibilities:
Build advanced machine learning models, including deep learning models, gradient boosting machines, time series models, statistical models and clustering analysis based on project requirements.
Check model stability, model optimization and model performance measurements and perform exploratory data analysis, feature selection, and data visualization.
Design, document, develop, code, and test advanced analytics models into scalable advanced analytics solutions.
Develop frameworks for tracking and measuring results produced by analytics models.
Research new machine learning techniques and advanced analytics solutions and implement them on Ether, our Machine Learning and Artificial Intelligence based platform.
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