JPMorgan Data Domain Architect Vice President 

United States, Ohio 

655095545

As a Data Domain Architect, Vice President in the Finance Decision Optimization group, you will actively collaborate with various stakeholders and functional teams to determine data and model requirements for constructing data pipelines and compiling complex predictive and optimization routines into executable Python packages for prototype QA testing and production deployment. This role provides an opportunity to apply your data science, data engineering, and Python machine learning application development skills in a dynamic and competitive environment.

Job responsibilities

• Building and compiling data pipelines, complex predictive models and optimization routines into executable packages for prototype QA testing and production deployment.
• Assisting in solution back testing exercises for Fair Lending and other key stakeholders.
• Conducting transaction data analyses with big data technologies on Cloud platforms and turn massive amounts of data into actionable insights that drive business value.
• Creating opportunities to automate repeatable analysis for the business.
• Working on cross functional teams and collaborate with internal and external stakeholders.
• Proactively raise critical issues to the business and technology partners.
• Keeping abreast of industry trends and provide recommendations for testing new and emerging technology.
• Supporting ongoing technology evaluation process and proof of concept projects.
• Keeping up with project delivery timelines and meet critical business needs.

Required qualifications, capabilities and skills

• A minimum of 8 years of relevant professional experience as a software developer, data/ML engineer, data scientist, or business intelligence engineer.
• A Bachelor's degree in Computer Science, Financial Engineering, MIS, Mathematics, Statistics, or another quantitative field.
• Practical knowledge of the banking sector, specifically in areas of retail deposits, auto, card, and mortgage lending.
• Exceptional problem-solving abilities, coupled with a clear understanding of business requirements. Must be able to effectively communicate complex information to a wide range of audiences.
• Must be highly detail-oriented, with a proven track record of delivering tasks on schedule.
• A proven track record of success, as demonstrated by professional or educational achievements.
• Eagerness to stay updated with the latest advancements in cloud data technologies and machine learning.

Preferred qualifications, skills and capabilities

• Proficiency in Python programming, with a strong understanding of object-oriented and functional programming concepts, and its application in data processing and machine learning.
• Expertise in Linux bash shell command environment and Git for version control and collaborative coding.
• Advanced SQL skills for complex query writing, data manipulation, and analysis, coupled with strong experience in data engineering, including ETL processes.
• Proficiency with the Anaconda ecosystem, including Pandas, NumPy, and SciPy, and practical experience integrating and implementing machine learning algorithms using TensorFlow and XGBoost.
• Extensive knowledge of Apache Spark, with experience optimizing Spark jobs for performance and scalability within Databricks, and hands-on experience with AWS EC2, EMR environments, and S3/EFS storage.
• Ability to analyze data using tools such as Tableau and Alteryx to develop and automate reports or analyses that lead to actionable business insights, along with experience in data analysis, cleansing, modeling (including machine learning, time series, NLP), and visualization.
• Knowledge of data modeling, data governance, and compliance standards relevant to handling sensitive data and familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes)