Machine Learning Operations (MLOps) Engineer

Job Description:

• Manage big data initiatives for the Data Science and AI Group while working closely with the technology team, vendors, and consultants
• Coordinate with business and technology stakeholders to ensure that requirements are implemented as expected
• Facilitate implementation of analytical tools
• Recommend and maintain the data model that will support business intelligence, advanced analytics, and campaign management initiatives
• Implement enhancements in the existing MLOps pipeline
• Establish data quality checks to identify integrity issues and report findings to technology management for resolutions
• Establish and implement data governance guidelines to ensure delivery of high quality and secure data to meet regulatory requirements and promote efficiency and revenue growth
• Establish a catalog of commonly used data fields to aid data users in exploring the banks data, improve the understanding of data across the bank, and promote consistency of KPI definition
• Conduct best practice research to continuously improve current data management and analytics processes and ensure data management and analytics tools/processes are at par with global standards
• Conduct POC on new solutions

Qualifications:

Proficient in data processing tools (SQL, Python, R)

Strong knowledge of batch and stream data processing techniques (Spark, Kafka)

Strong knowledge in MLOps and related concepts

Experienced in data modelling and data warehousing techniques

Experienced in using Git for version control and CI/CD

Experienced in using business intelligence tools (Power BI, Tableau)

Preferably with experience in Cloudera and Snowflake

Preferably with experience in the banking and financial services industry