Analytics Engineer

• Design, develop, install, deploy, test, medium-scale analytics models and AI applications in support of business and client outcomes and objectives.
• Design and implement training pipelines for machine learning models.
• Build leading MLOps pipelines to deploy and update machine learning models and analytics applications.
• Build leading feature engineering pipelines extracting and preparing data for machine learning model performance.
• Train and evaluate models using diverse datasets and performance metrics, choosing and applying appropriate machine learning algorithms.
• Maintain and optimize model to improve accuracy and monitor reliability.
• Implement leading monitoring mechanisms to track model performance and identify issues.
• Detect and mitigate biases in machine learning models to promote fairness.
• Write leading specifications of machine learning models and processes for reproducibility and maintenance.
• Present insights and performance tuning recommendations from machine learning models to inform business decisions.
• Promote ethical principles and responsible AI guidelines for machine learning development.
• Integrate machine learning models into production environments.
• Develop and deploy APIs for model access and prediction requests.
• Leverage best practices and patterns in MLOps (machine learning operations) to ensure efficient and scalable model lifecycle management.
• Integrate leading AI service and machine learning models with existing applications and DevSecOps deployment pipelines.
• Embrace Agile development practices and employ SDLC processes on all development.
• Collaborate with data scientists practitioners, finance and business analysts, actuaries and engineers to achieve model objectives.
• Effectively mentor other engineers.
• Lead a "data-first" approach to problem solving and designing IT solutions.

Principal ML Analytics Engineer

• Support ongoing implementation of the Reporting Standards across Northern Trust
• Standardize controls and issues reporting across governance forums
• Create and maintain data maps and data dictionaries
• Produce regular and ad-hoc reports as needed
• Identify and escalate complex challenges and articulate actionable plans

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Principal ML Analytics Engineer

Technology/Data Analytics Specialist – Chief Control Office