Overview

Career Area: Technology, Digital and Data

Responsibilities

• Explore, implement and deploy pipelines for deep learning, neural networks, chatbots, and image processing solutions.
• Collaborate with cross-functional teams to deliver high-quality AI projects.
• Tracking of multiple models, experiments for auditing purpose
• Collaborate with data scientists for hyper parameter tuning and features maintenance
• Model management and versioning
• Work with infra team, data scientists, business in establishing artifact lineage, model registry, governance
• Assist in testing, automated deployment
• A pipeline for triggering retraining to detect model drift or data drift, trigger retraining
• Working knowledge of AWS Lambda, Sagemaker, AWS Step Functions
• Must To Have Skills: Proficiency in Machine Learning Operations.
• Creation of CI,CD Pipelines for ML algorithms, training, prediction pipelines
• Work with business, data scientists to ensure value realization, ROI on operationalization of models
• Strong understanding of statistical analysis and machine learning algorithms.
• Containerization, packaging of ML models
• Endpoint creation for prediction
• Experience with data visualization tools such as Tableau or Power BI.
• Hands-on experience implementing various machine learning algorithms.
• Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity.
• Helps create contingency plans to mitigate impact of disruption on core applications.
• Identifies key players, criticalities, roles, and responsibilities.
• Investigates application-related issues with both business and IT professionals.
• Recommends enhancements for a major application system or related subsystems.
• Works with core application systems for a major business unit or function.
• Identifies and documents specific problems and resolution alternatives.
• Examines a specific problem and understands the perspective of each involved stakeholder.
• Develops alternative techniques for assessing accuracy and relevance of information.
• Helps to analyze risks and benefits of alternative approaches and obtain decision on resolution.
• Uses fact-finding techniques and diagnostic tools to identify problems.
• Analyzes system requirements and translates them into detailed design specifications.
• Designs complex application architectures that meet performance, scalability, and reliability requirements.

Qualifications

• Follows policies, practices and standards for determining functional and informational requirements.
• Confirms deliverables associated with requirements analysis.
• Communicates with customers and users to elicit and gather client requirements.
• Participates in the preparation of detailed documentation and requirements.
• Utilizes specific organizational methods, tools and techniques for requirements analysis.
• Assists with current and planned integration initiatives.
• Explores major issues and considerations for successful system integration.
• Works with applications, data, technology bridges and a variety of platforms.
• Works with existing interfaces as well as integration and migration plans within own area.
• Plays an active role in local integration efforts.
• Supports the project leader in developing and executing system test plans.
• Evaluates system documentation and user manuals for usability, accuracy and completeness.
• Executes test cases, analyzes test results and reports on findings regularly.
• Tests system components for compliance with functional requirements.
• Participates in the testing of a system's ability to recover from hardware or software failures.