Machine Learning Engineer

Mission:

• To improve data quality and consistency throughout the data migration process by leveraging machine learning techniques.
• To collaborate across departments to implement data quality metrics, identify and resolve data issues, and ensure data is effectively used.
• To develop and integrate machine learning solutions to automate tasks, improve efficiency, and enhance data security and compliance.

Roles & Responsibilities:

• To develop and implement data quality metrics with management’s guidance, monitor data quality over time, and identify and resolve data quality issues by cross-functional collaboration to ensure data quality standards are met and data is effectively used to drive business value, leveraging machine learning techniques where applicable.
• To support digital transformation initiatives in the data dimension by identifying opportunities to leverage big data technologies for business value, with a focus on integrating machine learning solutions.
• To evaluate and suggest appropriate machine learning techniques and algorithms based on data characteristics and product migration requirements to enhance data quality and consistency.
• To conduct data profiling and exploratory analysis to identify data quality issues, patterns, and anomalies impacting the product migration process and utilize machine learning algorithms for advanced analytics.
• To collaborate with data engineers for the design and implementation of data pipelines for seamless data transfer between systems; while maintaining data consistency and incorporating machine learning methodologies where applicable.
• To develop monitoring and alerting systems to track migration progress and detect errors or issues in real-time, ensuring data consistency across different databases and systems through machine learning-based anomaly detection.
• To test and validate migrated data to ensure accuracy, completeness, quality, and consistency by leveraging machine learning algorithms.
• To provide technical support to project teams and stakeholders throughout the data migration lifecycle, ensuring data consistency is maintained across all stages through the application of machine learning techniques.
• To troubleshoot and resolve data-related challenges encountered during the data migration process, including but not limited to data format compatibility, data loss, and performance issues, utilizing machine learning for data analysis and problem-solving.
• To effectively collaborate with IT and security teams to ensure data privacy and compliance with regulatory requirements during migration, while maintaining data consistency through machine learning-driven security measures.
• To develop automation scripts and tools to streamline repetitive tasks and improve the efficiency of the data migration process, with a focus on machine learning-driven automation solutions.
• To conduct post-migration analysis to evaluate the effectiveness of the migration process and identify areas for improvement, leveraging machine learning for insights generation and optimization.
• To evaluate third-party tools and solutions for data migration and machine learning, providing input based on project requirements, ensuring compatibility and data consistency with machine learning-driven solutions.
• To develop data migration standards, methodologies, and best practices within the organization, emphasizing the importance of data consistency and the integration of machine learning technologies.
• To build and maintain effective relationships with external vendors and partners to leverage expertise and resources for data migration projects, ensuring alignment with data consistency goals and the integration of machine learning capabilities.
• To identify risks and dependencies related to data migration activities, utilizing machine learning for risk assessment and mitigation, and also to contribute to developing mitigation strategies to minimize impact on project timelines and objectives while ensuring data consistency is preserved,.
• To collaborate with team members and different departments to explore potential machine learning applications, ensuring they align with business objectives and priorities and facilitate the process.
• To develop machine learning models to examine and verify data integrity during the migration process. This involves identifying irregularities and inconsistencies to prevent data loss or corruption and maintain data consistency.
• To automate tasks related to data mapping and transformation, using machine learning algorithms to reduce manual workload and speed up the migration process for various products while maintaining data consistency and integrity.
• To actively identify and resolve issues to minimize disruptions to daily business operations and prevent potential data loss.
• To utilize machine learning algorithms for data monitoring and auditing tools to evaluate data quality and integrity post-migration continuously, which ultimately helps maintain data consistency and prevent data loss over time.
• To integrate machine learning technologies and methodologies throughout the organization; advocating for a data-driven approach and implementing data management and migration process changes to prevent data loss, maintain data consistency, and enhance business value.

Education:

• Bachelor’s Degree in Information Technology or related
• MBA/Master’s degree is advantageous

Experience:

• Technical data handling tracks record of 3 years or more; with at least one year in telecommunication related Business (CVM, BI, Data engineering, and Data Science)
• 2 years of experience in managing a portfolio of technical and business projects
• Worked across diverse cultures and geographies is advantageous

Technical Competencies:

• Data Architecture
• Requirement Analysis
• Database Management
• Big Data Platforms
• Reporting and Analysis
• Data Visualization & Presentation
• Strategy Management
• Machine learning
• Programming Languages
• Business Intelligence
• Distributed Computing
• Statistical Analysis
• Data Quality Assurance

Behavioral Competencies:

• Lead with care
• Can-do with integrity
• Serve with respect
• Collaborate with agility
• Act with inclusion