Credit Risk Analytics Manager Jobs in Modesto, CA

POSITION PURPOSE

The Data Architect is a critical founding role responsible for transforming Mocse's data from a fragmented resource into a strategic asset. This role will establish automated reporting capabilities, build data governance foundations, develop advanced analytics, and drive continuous experimentation and optimization. This is a high-impact, high-visibility position reporting to the Vice President of Performance and Risk and working closely with executive leadership to make Mocse a truly data-driven organization.

ESSENTIAL JOB FUNCTIONS

Data Access & Reporting

1. Automated Reporting & Analytics
   1. Design, develop, and automate reports that deliver critical information to operational groups and provide analytics and KPIs for leadership
   2. Reduce report turnaround times and enable self-service access to data
   3. Create and maintain dashboards for executives, department heads, and business users
   4. Establish refresh schedules and monitoring procedures for all reporting
   5. Migrate and optimize reports as systems and platforms evolve
2. Data Integration & Management
   1. Integrate disparate data sources across multiple database platforms (core banking, lending platform, digital platform, card systems)
   2. Create direct connections to source systems and build automated data pipelines
   3. Design standardized data models for member, account, and transaction entities
   4. Determine appropriate software tools based on assignment goals
   5. Document all transformations, data lineage, and business rules

Data Governance & Quality

1. Data Documentation & Governance
   1. Catalog and document data sources, definitions, and business rules across all systems
   2. Assess and monitor data quality; identify and resolve data issues
   3. Support the Data Governance Council and implement governance policies
   4. Develop and maintain data classification schema and access control principles
   5. Ensure compliance with NCUA, FFIEC, CCPA, GLBA, and Right to Financial Privacy Act requirements
   6. Draft and maintain documentation of procedures for generating reports and accessing data

Advanced Analytics & Insights

1. Strategic Analysis & Predictive Analytics
   1. Research and analyze data trends to identify areas of opportunity and inform strategic decision-making
   2. Develop predictive models for member churn, loan default risk, fraud detection, and lifetime value
   3. Create member segmentation and personalization analytics for targeted marketing
   4. Build operational intelligence including anomaly detection, process optimization, and forecasting
   5. Perform demographic and geographic analysis to contribute to operations and marketing planning
2. Risk Management & Fraud Analytics
   1. Develop real-time fraud monitoring dashboards and transaction anomaly detection
   2. Create member risk segmentation and geographic risk analysis
   3. Support compliance reporting and audit requirements
   4. Monitor data security and privacy controls
3. Member Experience Analytics
   1. Build 360-degree member views combining all product relationships
   2. Develop member journey analytics across channels
   3. Create churn prediction and early warning indicators
   4. Analyze product affinity and identify cross-sell opportunities
   5. Track member satisfaction, NPS, and experience metrics
4. Operational Efficiency Analytics
   1. Measure process cycle times (loan approval, account opening, etc.)
   2. Analyze channel utilization and cost per transaction
   3. Track employee productivity metrics and branch performance
   4. Monitor system performance and data quality dashboards

Stakeholder Collaboration & Communication

1. Business Partnership & Requirements Gathering
   1. Work directly with stakeholders to identify analytical needs
   2. Translate business problems into data solutions
   3. Regularly update stakeholders on progress and recommend improvements
   4. Synthesize, visualize, and communicate complex information to diverse audiences
   5. Assist teams with targeting and campaign analytics

Continuous Improvement & Innovation

1. Platform Optimization & Experimentation
   1. Continuously optimize analytics platform performance and cost efficiency
   2. Experiment with new analytical techniques, tools, and methodologies
   3. Expand data integration and real-time capabilities as business needs evolve
   4. Develop APIs for data access by applications
   5. Stay current on BI tools, analytics best practices, and industry trends

Professional Development & Collaboration

1. 1. Enhance job performance by applying up-to-date professional and technical knowledge gained through training, publications, and professional relationships
   2. Participate in committee, community, and group projects as assigned
   3. Mentor others and build data literacy across the organization
   4. Contribute to attaining Credit Union objectives by accomplishing related results as assigned.

KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:

Technical Expertise (Must-Have)

1. Advanced SQL proficiency - Ability to write complex queries, optimize performance, and work across multiple database platforms
2. BI tool expertise - Hands-on experience with modern BI platforms (Power BI, Tableau, Looker, or similar)
3. Data integration skills - Proven ability to connect disparate data sources and build automated data pipelines
4. Advanced Excel proficiency - Pivot tables, advanced formulas, macros, Power Query
5. Data visualization mastery - Ability to create compelling, intuitive dashboards and reports for diverse audiences
6. Relational database understanding - Strong grasp of database design, normalization, and data modeling principles
7. Artificial intelligence - Ability to utilize AI comfortably to assist with Mocse's strategic initiatives

Preferred Technical Skills

1. Experience with Python, R, or SAS for statistical analysis and predictive modeling
2. Familiarity with cloud-based analytics platforms (AWS, Azure, Snowflake, or similar)
3. Knowledge of ETL/ELT processes and tools
4. Understanding of data governance frameworks and master data management
5. Experience with machine learning and predictive analytics

Business & Industry Knowledge

1. Financial services background strongly preferred - Credit union or banking experience is highly desirable
2. Understanding of core banking systems, lending platforms, and card processing systems
3. Familiarity with fraud detection, risk management, and regulatory compliance requirements
4. Knowledge of member lifecycle analytics and retention strategies

Core Competencies

1. Self-starter mentality - Ability to work independently with minimal supervision and take ownership of deliverables
2. Excellent communication skills - Written, oral, and presentation abilities to communicate complex data insights to non-technical stakeholders
3. Analytical and problem-solving skills - Ability to identify root causes, spot trends, and recommend actionable solutions
4. Project management capability - Strong organizational skills, ability to prioritize competing demands, and deliver results
5. Attention to detail - Work accurately with close attention to data quality and report accuracy
6. Adaptability and experimentation mindset - Comfortable with ambiguity, excited by experimentation, and able to pivot quickly based on business needs
7. Collaboration - Ability to build relationships across departments and influence without authority
8. Ethical conduct - Demonstrates highest level of integrity when handling confidential member and business data
9. Initiative and continuous improvement orientation - Takes proactive action, anticipates needs, and continuously seeks optimization opportunities
10. Ability to maintain confidentiality of sensitive member and business information
11. Professional demeanor - Exhibits a professional, businesslike appearance and approach

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QUALIFICATIONS:

Required

• Bachelor's degree in a quantitative field - Business Information Systems, Computer Science, Data Analytics, Statistics, Finance, Mathematics, Engineering, or related field
• Minimum 3-5 years of hands-on experience in business intelligence, data analytics, or reporting roles
• Proven track record of delivering automated reporting solutions and building analytics capabilities
• Demonstrated experience working with multiple data sources and integrating disparate systems
• Must be bondable

Strongly Preferred

• Financial services experience - Credit union or banking background
• Data governance experience - Participation in data quality, documentation, or governance initiatives
• Cloud analytics platform experience - Modern BI and cloud data warehouse implementations
• Predictive analytics experience - Building and deploying machine learning models
• Professional certifications - Microsoft Certified Data Analyst, Tableau Desktop Specialist, or similar