Principal Data Analyst - Retail Bank
AI summary of the role
Principal Data Analyst in Retail Bank leverages advanced analytics to innovate data solutions, deliver business intelligence, and manage data quality across digital banking, operations, payments, and small business segments.
What you’ll do
- Mine complex data sources using Python, R, Spark, SQL
- Build self-service data tools and dashboards for business insights
- Drive data quality management, metadata, lineage, governance
- Partner with business to translate needs into analytics solutions
What you’ll bring
- Bachelor’s + 5 years or Master’s + 3 years data analytics experience
- 3+ years scripting in Python, R, Spark, or SQL
- 3+ years BI visualization tools
- 3+ years querying/analyzing data platforms
Technologies
Python · R · Spark · SQL · AWS · data warehouses
Source and classification
Internal deployment & tooling · Evidence for this classification:
business and functional areas include digital/online banking, branch/cafe experience, bank operations (i.e., account maintenance, deposits, ATM, tax reporting, etc.), contact center, enterprise payments (debit, ACH, check, wires, etc.), marketing and product strategy, and small business banking (i.e., strategy and deposits, sales and servicing, and lending). As a Data Analyst at Capital One you will leverage analytic and technical skills to innovate, build, and maintain well-managed data solutions and capabilities to tackle business problems. On any given day you will be challenged on three types of work – Innovation, Business Intelligence and Data Management: Innovation Use Open Source/Digital technologies to mine complex, voluminous, and different varieties of data sources and platforms Build well-managed data solutions, tools, and capabilities to enable self-service frameworks
More from the job description
Principal Data Analyst - Retail Bank At Capital One, data is at the center of everything we do. When we launched as a startup we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. In the Consumer Bank, we’ve combined this human-centered approach with our heritage of data-driven decision making to design, build and test our way to truly enabling financial experiences. We’ve challenged ourselves to spend less time planning, more time doing, and, above all else, to see the world through the eyes of our customers as they work to understand and manage their money. Retail Bank line of business and functional areas include digital/online banking, branch/cafe experience, bank operations (i.e., account maintenance, deposits, ATM, tax reporting, etc.), contact center, enterprise payments (debit, ACH, check, wires, etc.), marketing and product strategy, and small business banking (i.e., strategy and deposits, sales and servicing, and lending). As a Data Analyst at Capital One you will leverage analytic and technical skills to innovate, build, and maintain well-managed data solutions a [... source excerpt omitted ...] , Spark, and SQL) Strong desire and experience with data in various forms (data warehouses/SQL, unstructured data) Experience utilizing and developing within AWS services Basic Qualifications: Currently has, or is in the process of obtaining a Bachelor’s Degree in quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related quantitative field) plus at least 5 years of experience performing data analytics, or, a Master’s Degree plus at least 3 years performing data analytics with an expectation that required degree will be obtained on or before the scheduled start date. At least 3 years of experience working with at least one [... source excerpt omitted ...] of experience utilizing a business intelligence visualization tool At least 3 years of experience in querying, analyzing and working with data languages and platforms Preferred Qualifications: Master’s Degree in a Science, Technology, Engineering, Mathematics discipline At least 4 years of experience coding in Python, R, Spark, or SQL At least 4 years of experience working within process management and improvement methodologies – Agile, Lean, Six Sigma, etc. At least 2 years of experience utilizing and developing within AWS services At least 2 years of experience delivering Data Governance and Data Quality Management concepts and practices within the financial services industry
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