JPMorgan Machine Learning / Data Analytics - Lead Software Engineer 

United States, Ohio, Columbus 

797514737

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Effectively collaborate with business stakeholders and Data Scientists to dive deep into the data and extract key insights
• Identify and implement best practices in machine learning to interpret data with special focus on anomaly detection
• Proven hands on experience creating and implementing machine learning applications on the Cloud (Databricks/AWS)
• Show understanding of data relationships (Logical and Physical models)
• Create an end to end system architecture for a Data Analytics application
• Develops secure high-quality production code, and reviews and debugs code written by others
• Manage building system designs for data pipelines geared towards analytics
• Manage business stakeholder, understanding key business requirements and creating system design would be required

Required qualifications, capabilities, and skills

• Formal training or certification on data engineering and machine learning concepts and 5+ years of applied experience
• Prior experience working with Databricks Lakehouse architecture dealing with high volume relational data
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Demonstrate ability to create Data Pipelines using Python libraries such as PySpark, Pandas, NumPy
• Experience with Modern Analytics tools such as Looker, Thoughtspot, Tableau, Quik Sense
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies
• In-depth knowledge of the financial services industry and their IT systems
• Practical AWS cloud native experience

Preferred qualifications, capabilities, and skills

• Prior experience working with Anomaly Detection models
• Extensive experience working with Data Science teams to develop, train, test and deploy AI/ML applications
• Experience in AI particularly working with Large Language Models