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The Applications Development Intermediate Programmer Analyst is an intermediate level position responsible for participation in the establishment and implementation of new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to contribute to applications systems analysis and programming activities.
Job Responsibility:
Acts as SME to senior stakeholders and/or other team members
Utilize knowledge of applications development procedures and concepts, and basic knowledge of other technical areas to identify and define necessary system enhancements, including using script tools and analyzing/interpreting code
Consult with users, clients, and other technology groups on issues, and recommend programming solutions, install, and support customer exposure systems
Apply fundamental knowledge of programming languages for design specifications
Analyze applications to identify vulnerabilities and security issues, as well as conduct testing and debugging
Serve as advisor or coach to new or lower level analysts
Identify problems, analyze information, and make evaluative judgements to recommend and implement solutions
Resolve issues by identifying and selecting solutions through the applications of acquired technical experience and guided by precedents
Operate with a limited level of direct supervision
Exercise independence of judgement and autonomy
Appropriately assess risk when business decisions are made, driving compliance with applicable laws, rules and regulations, adhering to policy, applying sound ethical judgment, and escalating or managing issues with transparency
Requirements:
4-8 years of relevant experience in the Financial Service industry
DevOps Engineer with experience in Python, Shell, Bash Scripting
Expertise in CI/CD pipeline automation & related tools
Familiarity with CI/CD tools such as GitHub or Jenkins in the ML/AI context
AI related automation
Experience in building and iterating on supervised and unsupervised models using Python, scikit-learn, PyTorch, TensorFlow and organization approved models
Experience with MLOps tools and practices
Comfortable with Docker, Kubernetes, and cloud infrastructure
Experience in evaluating the impact and performance of models in test and production environments
Knowledge of High Value Payments, CBFT, RTGS is preferred
Consistently demonstrates clear and concise written and verbal communication
Demonstrated problem-solving and decision-making skills
Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements
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