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This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
The role of a VP Java Full Stack Engineer with Data Science expertise is multifaceted and dynamic. This VP will be responsible for overseeing the entire spectrum of full stack development projects, with a particular focus on Java technologies. Integrating data science into full stack development is a key aspect of this role, ensuring that analytical insights drive development processes and enhance overall functionality.
Data science plays a crucial role in transforming vast amounts of data into actionable insights, thereby informing and optimizing development practices. The VP must ensure that all projects adhere to the stringent compliance frameworks mandated by Consent Orders and Article V, which often involve legal and regulatory guidelines that govern organizational operations.
Key Responsibilities
The primary responsibilities of the VP Java Full Stack Engineer with Data Science expertise include leading comprehensive development projects and ensuring seamless data science integration. This entails:
-Leading Development Projects: Overseeing full stack development initiatives, with a strong emphasis on Java, and ensuring successful project delivery.
-Data Science Integration: Guiding data science efforts, ensuring they align with and support overall software development processes.
-Compliance Adherence: Guaranteeing that all projects comply with the requirements of Consent Orders and Article V, which involves meticulous attention to legal and regulatory standards.
-: Leading the charge on adopting new technologies and staying updated with industry best practices and trends.
Required Skills and Qualifications
-Proficiency in Java Development: Extensive experience with Java and full stack development technologies.
-Data Science Expertise: Strong analytical skills and significant experience in data science, including data management, analytics, and machine learning.
-: Familiarity with regulatory requirements related to Consent Orders and Article V, ensuring that development practices meet these standards.
Experience and Education
-Extensive Industry Experience: At least 10+ years of experience in software engineering and data science, with a strong track record of leading and delivering complex projects.
-: An advanced degree in Computer Science, Data Science, or a related field is highly desirable, reflecting a deep understanding of both technical and analytical domains.
Applications Development
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