Lead Scientist, Analytic Science

Role Overview: Join a team at FICO that utilizes cutting-edge technology to solve problems with analytics, focusing on Artificial Intelligence (AI) and Machine Learning (ML). As a member of this team, you will work on building industry-leading solutions, collaborating with analytical and engineering experts who share a passion for innovation. If you are a problem solver who enjoys tackling tough challenges using data and analytics, this is the place for you. Key Responsibilities: - Work with real-world data, ensuring data quality at every stage of acquisition and processing, including collection, normalization, and transformation. - Research and select suitable statistical methods and computational algorithms. - Develop high-end analytic models for relevant problems using statistical modeling techniques, managing projects under time constraints and collaborating with other teams for integration and deployment of analytics software and solutions. - Assist in model go-lives by conducting production data validations and analyzing models in production. - Participate in client meetings to investigate and resolve issues, applying data mining methodology in thorough analyses of model behaviors and supporting customer meetings, model construction, and pre-sales. Qualifications Required: - MS or PhD degree in computer science, engineering, physics, statistics, mathematics, operations research, or related fields with hands-on experience in predictive modeling and data mining. - Experience in analyzing large datasets, applying data-cleaning techniques, and performing statistical analyses to understand data structures. - Background in Machine Learning (ML) and Artificial Intelligence (AI) is preferred. - Demonstrable 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 and experience with languages such as Java, Python, C++, or C. - Hands-on experience working with Linux. (Note: No additional details about the company were provided in the job description) Role Overview: Join a team at FICO that utilizes cutting-edge technology to solve problems with analytics, focusing on Artificial Intelligence (AI) and Machine Learning (ML). As a member of this team, you will work on building industry-leading solutions, collaborating with analytical and engineering experts who share a passion for innovation. If you are a problem solver who enjoys tackling tough challenges using data and analytics, this is the place for you. Key Responsibilities: - Work with real-world data, ensuring data quality at every stage of acquisition and processing, including collection, normalization, and transformation. - Research and select suitable statistical methods and computational algorithms. - Develop high-end analytic models for relevant problems using statistical modeling techniques, managing projects under time constraints and collaborating with other teams for integration and deployment of analytics software and solutions. - Assist in model go-lives by conducting production data validations and analyzing models in production. - Participate in client meetings to investigate and resolve issues, applying data mining methodology in thorough analyses of model behaviors and supporting customer meetings, model construction, and pre-sales. Qualifications Required: - MS or PhD degree in computer science, engineering, physics, statistics, mathematics, operations research, or related fields with hands-on experience in predictive modeling and data mining. - Experience in analyzing large datasets, applying data-cleaning techniques, and performing statistical analyses to understand data structures. - Background in Machine Learning (ML) and Artificial Intelligence (AI) is preferred. - Demonstrable 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 and experience with languages such as Java, Python, C++, or C. - Hands-on experience working with Linux. (Note: No additional details about the company were provided in the job description)