Business Analytics Manager at PNC managing email marketing campaigns and leading analytics initiatives. Collaborating across teams to optimize engagement and deliverability while ensuring compliance in marketing.
FT
Hybrid Data Visualization Analyst – Credit Focus, GCP
Posted last week
About the role
- Data Visualization Analyst developing dashboards and insights in the financial sector using Google Cloud Platform and Python. Requires expertise in credit analytics and data storytelling.
Responsibilities
- Develop advanced data visualizations in Looker Studio, creating dashboards that monitor credit KPIs (e.g., approval rate, delinquency/overdue, vintages/origination cohorts, recovery, and risk exposure).
- Conduct exploratory and descriptive analyses to identify customer behavior patterns, anomalies in credit workflows, and opportunities to optimize the portfolio.
- Build and maintain data pipelines consuming APIs and diverse sources, ensuring data is available and cleansed in the Cloud environment.
- Operate within Google Cloud Platform (GCP), using BigQuery primarily as the data warehouse for data modeling geared toward visualization.
- Use Python to handle large volumes of data (Pandas/NumPy), automate reports, and ingest data via scripts.
- Interface directly with Data Engineering and Credit Risk teams to define metrics and data requirements and to align on data infrastructure.
Requirements
- Credit experience: Deep knowledge of credit metrics and risk analysis (vintage/cohort analysis, provision for doubtful accounts (PDD), churn, scoring models, etc.).
- Looker Studio: Advanced proficiency with the tool (calculated fields, data blends, and user experience design).
- Python: Fluent for data analysis and integration (libraries: Pandas, Requests, SQLAlchemy).
- Google Cloud Platform (GCP): Hands-on experience with BigQuery (advanced SQL) and familiarity with Cloud Storage and Cloud Functions.
- APIs and Integrations: Proven experience connecting data sources via API (JSON/REST) and implementing ETL/ELT processes.
- Descriptive Statistics: Solid foundation in statistics to interpret means, quartiles, dispersion, and trends.
- Google Cloud certifications (e.g., Cloud Digital Leader or Data Engineer).
- Version control tools (Git).
- Experience with dbt (data build tool) for modeling in BigQuery.
- Knowledge of Looker (Enterprise/LookML).
Benefits
- Position also open to candidates with disabilities
Job title
Job type
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Not specified
Degree requirement
No Education Requirement
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