CCB Risk Forecasting Transformation

Organization Description

Our Consumer & Community Banking  (CCB) division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

Risk Management helps the firm understand, manage and anticipate risks in a constantly changing environment. The work covers areas such as evaluating country-specific risk, understanding regulatory changes and determining credit worthiness. Risk Management provides independent oversight and maintains an effective control environment.

Job Description

We are seeking a dynamic and strategic forecasting transformation associate to drive the modernization and optimization of credit forecasting processes. This role will be responsible for leading cross-product initiatives to transform forecasting processes, integrate advanced analytics, and implement best-in-class tools and methodologies. The ideal candidate should possess a strong background in data pipeline management, process improvement and data analytics. The role involves working in partnership with model users (e.g., Loss Forecasting, Finance, Controller), Data Architecture and Technology, and Finance Automation & Execution (FAE) to enhance the end-to-end forecast across all retail products. You will establish best practices in data consumption and tools for reporting and analytics, resolve obstacles and drive discussions to achieve the target state, and support the implementation of the '1-click execution' vision across the Forecasting team.

Job responsibilities

• Streamline both model and non-model components processes and create comprehensive datasets (outputs) that will be used most of the time
• Assist the Forecasting team in automating non-model processes in Frame/Databricks
• 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
• Manage the delivery of transformation projects and communicate solutions, roadmaps, and progress to multiple stakeholders (Forecasting team, Project Management, Finance, Product Owner, and Technology) 
• Creating data pipelines to connect data sources to multiple tools for quicker analytics
• Automate and migrate legacy processes ensuring seamless execution and efficiency 
• Facilitate training and mentoring among peers on cloud capabilities and offerings, as well as analytical and reporting tools
• Ensure firm wide controls and governance are followed, escalate issues and risks appropriately, and collaborate with key stakeholders for resolution and recurrence prevention
• Foster an environment of continuous improvement 

Preferred qualifications, capabilities, and skills.

• 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
• Proficient in data aggregation and analytical/ML tools (e.g., SQL, Python, PySpark)
• Experience with both structured and unstructured data, as well as semantic layers and cube dimensions
• Familiarity with cloud offerings and capabilities such as S3 Bucket, EMR, SageMaker, Databricks, and data catalog tools
• Knowledge of Agile/Productivity tools (e.g., JIRA, Confluence, GitHub)
• Experience in prompt creation to leverage in house LLM suites 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