Data Engineering (ML Ops) - Analyst

Job Description Role Overview: You are applying for the position of Data Engineering Analyst at JPMorgan Chase & Co. within the Global Services team in Bangalore. As a part of the Commercial Banking (CB) Line of Business-aligned finance & business support team, you will be responsible for assisting the data analytics team agenda, building new ML capabilities, developing and deploying ML models for metrics/management reporting, and providing decision support. You will work on high-impact initiatives that drive profitability and efficiency across the Commercial Banking organization. Key Responsibilities: - Work extensively with team data scientists to document and deploy models - Interact with external Model Ops teams to get models approved and deployed per JP Morgan Chase policies and regulations - Partner with senior leaders to advance the business analytics agenda focused on insights delivery in areas such as operational efficiency, cost modeling, capacity planning, and quality enhancements - Define, design, and drive high-priority strategic initiatives with senior-level visibility - Develop a deep understanding of systems and processes to extract insights from existing data and recommend IT enhancements for data quality improvement - Develop strong partnerships with IT application owners and data management teams to align on a roadmap for continual improvement - Provide support for in-flight projects - Deliver data insights, business value, and recommend next steps to senior stakeholders - Effectively communicate insights and recommendations verbally and in writing - Assist in setting up pipelines and deploying models - Collaborate with the team in designing and building machine learning algorithms Qualifications Required: - Bachelors/masters degree in economics, Econometrics, Statistics, or Engineering - 3 to 5 years of experience, preferably in financial services or commercial banking - Strong Python experience - Exposure to Cloud computing platforms like AWS, specifically AWS Sagemaker - Experience with Airflow and DAG development - Proficiency in data querying techniques such as SQL, Hadoop, HIVE, and AWS - Familiarity with Atlassian tools JIRA and Confluence - Ability to learn new capabilities and technologies in the evolving job landscape - Experience in CI/CD deployment environment with Bitbucket and Jules being a plus - Banking & Financial Services background or experience is preferred - Cloud Practitioner, Dev Ops Engineer, or Solutions Architect certification would be advantageous - Understanding of JP Morgan model risk policies and procedures - Knowledge of modeling techniques like Regression, Time series, Clustering, and NLP - Working knowledge of Tableau - Experience in ServiceNow & JIRA is a plus (Note: Additional details of the company have been omitted as they were not explicitly mentioned in the provided job description.) Role Overview: You are applying for the position of Data Engineering Analyst at JPMorgan Chase & Co. within the Global Services team in Bangalore. As a part of the Commercial Banking (CB) Line of Business-aligned finance & business support team, you will be responsible for assisting the data analytics team agenda, building new ML capabilities, developing and deploying ML models for metrics/management reporting, and providing decision support. You will work on high-impact initiatives that drive profitability and efficiency across the Commercial Banking organization. Key Responsibilities: - Work extensively with team data scientists to document and deploy models - Interact with external Model Ops teams to get models approved and deployed per JP Morgan Chase policies and regulations - Partner with senior leaders to advance the business analytics agenda focused on insights delivery in areas such as operational efficiency, cost modeling, capacity planning, and quality enhancements - Define, design, and drive high-priority strategic initiatives with senior-level visibility - Develop a deep understanding of systems and processes to extract insights from existing data and recommend IT enhancements for data quality improvement - Develop strong partnerships with IT application owners and data management teams to align on a roadmap for continual improvement - Provide support for in-flight projects - Deliver data insights, business value, and recommend next steps to senior stakeholders - Effectively communicate insights and recommendations verbally and in writing - Assist in setting up pipelines and deploying models - Collaborate with the team in designing and building machine learning algorithms Qualifications Required: - Bachelors/masters degree in economics, Econometrics, Statistics, or Engineering - 3 to 5 years of experience, preferably in financial services or commercial banking - Strong Python experience - Exposure to Cloud computing platforms like AWS, specifically AWS Sagemaker - Experience with Airflow and DAG development - Proficiency in data querying techniques suc