Ccb Risk Credit Forecasting Transformation

JPMorgan Chase JPMorgan Chase · Banking · Bengaluru, Karnataka, India · Consumer & Community Banking

This role focuses on transforming and optimizing credit forecasting processes within JPMorgan Chase's Consumer & Community Banking division. It involves integrating advanced analytics, implementing new tools and methodologies, and leveraging prompt engineering with GenAI capabilities. The associate will work on streamlining processes, automating tasks in Databricks, creating data pipelines, and managing transformation projects. Key responsibilities include defining requirements for semantic layers, enabling AWS services for analytics, and ensuring adherence to firm-wide controls and governance. The role also involves facilitating training on cloud capabilities and analytical tools.

What you'd actually do

  1. Streamline both model and non-model components processes and create comprehensive datasets (outputs) that will be used most of the time
  2. Assist the Forecasting team in automating non-model processes in Databricks
  3. Collaborate with multiple stakeholders to define requirements for a semantic layer or reporting cube for easy retrieval of overlays and reporting processes; enable AWS services and capabilities for fine-grain forecast analytics
  4. Manage the delivery of transformation projects and communicate solutions, roadmaps, and progress to multiple stakeholders (Forecasting team, Project Management, Finance, Product Owner, and Technology)
  5. Creating data pipelines to connect data sources to multiple tools for quicker analytics

Skills

Required

  • Proficient in data aggregation and analytical/ML tools (e.g., SQL, Python, PySpark)
  • Familiarity with cloud offerings and capabilities such as S3 Bucket, EMR, SageMaker, Databricks, and data catalog tools
  • Experience in prompt creation to leverage in house LLM suites, Copilot and other GenAI capabilities for code rewrite and analytics
  • Proficiency in MS Office (Excel, Word, PowerPoint, Visio) for creating procedures, process maps, and data analysis
  • Ability to present findings and recommendations to senior management and other stakeholders

Nice to have

  • 4+ years of experience with strong problem-solving and interpersonal skills: a highly motivated, proactive, team player, confident in challenging the status quo, able to manage multiple projects simultaneously, and ready to work in a fast-paced environment
  • Prior experience with forecast execution or analytics in finance, risk management, or a related capacity
  • Experience with both structured and unstructured data, as well as semantic layers and cube dimensions
  • Knowledge of Agile/Productivity tools (e.g., JIRA, Confluence, GitHub)

What the JD emphasized

  • prompt engineering
  • prompt creation to leverage in house LLM suites, Copilot and other GenAI capabilities

Other signals

  • integrate advanced analytics
  • implement best-in-class tools and methodologies
  • prompt engineering
  • enhance the end-to-end forecast
  • semantic layer or reporting cube
  • AWS services and capabilities for fine-grain forecast analytics
  • Creating data pipelines
  • Automate and migrate legacy processes
  • cloud capabilities and offerings
  • analytical and reporting tools
  • prompt creation to leverage in house LLM suites, Copilot and other GenAI capabilities