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Develop and deploy machine learning systems for multivariate anomaly detection, correlation analysis, causality discovery, and complex time-series pattern recognition. Responsibilities include real-time monitoring, adaptive thresholding, automated alert prioritization, correlation-based clustering, dashboards, model performance tracking, and production integration. The role requires strong statistics, time-series analysis, ML engineering, distributed data processing, visualization, and MLOps experience.

Administer and support IBM Cognos TM1 and Planning Analytics environments across development, QA, and production. Responsibilities include installation, upgrades, monitoring, security, backups, recovery, troubleshooting, performance tuning, deployments, and stakeholder support for planning and forecasting. The role also develops and maintains Tableau dashboards, optimizes data sources, manages refresh schedules, and documents operational procedures. Experience with PAW, scripting, cloud platforms, SQL, and relational databases is advantageous.

Develop and maintain scalable full-stack web applications using Java, Python, and React. Build backend services, responsive interfaces, REST APIs, and microservices; collaborate with DevOps teams on AWS deployment and maintenance. Responsibilities include architecture contributions, code reviews, unit testing, documentation, CI/CD, troubleshooting, and production debugging. The role requires experience with Spring Boot, Hibernate, AWS services, relational and NoSQL databases, Git, and Docker.

Instructor-led AI and machine learning training covering theory, data preprocessing, algorithms, model building, analytics, real-time projects, case studies, and practical business and IT applications. Participants use Python, TensorFlow, and Scikit-learn and receive certification upon successful completion.

Develop and maintain scalable full-stack web applications using Java, Python, and React. Build backend services, responsive interfaces, REST APIs, and microservices; deploy and support applications on AWS. Collaborate with DevOps and cross-functional teams, contribute to architecture decisions, participate in code reviews and testing, document solutions, and troubleshoot production issues.