Analytic Science

Role Overview: As a Lead Scientist in the Analytic Science team at FICO, you will be part of a dynamic group that utilizes cutting-edge technology to solve real-world problems using Artificial Intelligence (AI) and Machine Learning (ML). You will collaborate with a team of analytical and engineering experts to build industry-leading solutions while having the opportunity to innovate and make a meaningful impact. Key Responsibilities: - Work with large volumes of real-world data, ensuring data quality at all stages of acquisition and processing, including data collection, normalization, and transformation. - Research and select appropriate statistical methods and computational algorithms for analytical modeling. - Build and oversee the development of advanced analytic models using statistical modeling techniques to address relevant problems. - Manage projects under time constraints and collaborate with cross-functional teams to integrate and deploy analytics software and solutions. - Perform production data validations and analyze models in production during model go-lives. - Assist in client meetings to investigate and resolve issues, apply data mining methodologies to analyze model behaviors, and provide support for customer meetings, model construction, and pre-sales activities. Qualifications Required: - MS or PhD degree in computer science, engineering, physics, statistics, mathematics, operations research, or natural science fields with substantial hands-on experience in predictive modeling and data mining. - Proficiency in analyzing large datasets, applying data-cleaning techniques, and conducting statistical analyses to understand data structures. - Background in Machine Learning (ML) and Artificial Intelligence (AI) is preferred. - Demonstrated experience in at least three of the following: neural networks, logistic regression, non-linear regression, random forests, decision trees, support vector machines, linear/non-linear optimization. - Strong programming skills with experience in Java, Python, C++, or C languages. - Hands-on experience working with Linux systems is desirable. (Note: The additional details of the company were not provided in the Job Description.) Role Overview: As a Lead Scientist in the Analytic Science team at FICO, you will be part of a dynamic group that utilizes cutting-edge technology to solve real-world problems using Artificial Intelligence (AI) and Machine Learning (ML). You will collaborate with a team of analytical and engineering experts to build industry-leading solutions while having the opportunity to innovate and make a meaningful impact. Key Responsibilities: - Work with large volumes of real-world data, ensuring data quality at all stages of acquisition and processing, including data collection, normalization, and transformation. - Research and select appropriate statistical methods and computational algorithms for analytical modeling. - Build and oversee the development of advanced analytic models using statistical modeling techniques to address relevant problems. - Manage projects under time constraints and collaborate with cross-functional teams to integrate and deploy analytics software and solutions. - Perform production data validations and analyze models in production during model go-lives. - Assist in client meetings to investigate and resolve issues, apply data mining methodologies to analyze model behaviors, and provide support for customer meetings, model construction, and pre-sales activities. Qualifications Required: - MS or PhD degree in computer science, engineering, physics, statistics, mathematics, operations research, or natural science fields with substantial hands-on experience in predictive modeling and data mining. - Proficiency in analyzing large datasets, applying data-cleaning techniques, and conducting statistical analyses to understand data structures. - Background in Machine Learning (ML) and Artificial Intelligence (AI) is preferred. - Demonstrated experience in at least three of the following: neural networks, logistic regression, non-linear regression, random forests, decision trees, support vector machines, linear/non-linear optimization. - Strong programming skills with experience in Java, Python, C++, or C languages. - Hands-on experience working with Linux systems is desirable. (Note: The additional details of the company were not provided in the Job Description.)