Anil Rayala

Worked across multiple LOBs to analyze and integrate data from diverse sources, created data pipelines, developed reports, and visualizations. Collaborated on a variety of financial products and services for consumers, small businesses, and commercial clients.

Finance Projects:

Fed-BIC Process: "Federal Reserve Borrower-in-Custody” program allows depository institutions (banks) to pledge their loans as collateral to the Federal Reserve for accessing the Discount Window while still retaining possession of the loan documents.

· Collected and integrated financial data from various sources, including Federal Reserve reports, regulatory filings, and economic datasets, for comprehensive and accurate data for analysis within the FED-BIC system.

· Conducted thorough analysis to validate the integrity of BIC codes and routing numbers. Worked on integrating auto and card products into the FED-BIC network.

· Automated data workflows using SQL, Python, Databricks and ETL tools to streamline both auto and card addition processes to reduce manual work.

· Regularly performed data quality checks, audits, and reconciliations on the data provided to the FED-BIC platform.

· Designed and developed interactive dashboards and financial reports using tools like AWS QuickSight, Tableau, and Excel, enabling stakeholders to monitor key economic trends, financial data, and performance metrics in real-time.

· Maintained documentation of data sources, processing steps, and methodologies to ensure transparency. Assisted with regulatory reports for audits concerning the addition of auto and card products within the FED-BIC process.

Simcorp: The Simcorp Project has been a significant initiative in 2024, aimed at enhancing data migration and integration processes between SUMMIT and Simcorp.

· Worked closely with diverse teams, to ensure the data migration to AWS S3 buckets and the construction of Parquet files align with business specifications.

· Utilized Parquet files to efficiently store and park large datasets, ensuring optimized storage and fast query performance.

· Took the initiative to become the Subject Matter Expert (SME) in Simcorp, which enabled me to contribute more to the project's success.

· Played a critical role in validating the QA dataset for IP, REPO, and DEBT data.

· Lead the data mapping process for all datasets from SUMMIT to SIMCORP. This involved a thorough analysis of both systems to facilitate seamless data integration.

· Developed and automated script’s using SQL, Python, Snowflake to monitor data consistency between SUMMIT and Simcorp which reduced the manual effort required for data validation. The automation sends real-time alerts for any inconsistencies, allowing for quick resolution.

· Processed and transformed Parquet files for analytical purposes, applying statistical models and machine learning algorithms to derive actionable insights from complex datasets.

Securitization: “securitization” process involves pooling various types of debt into a single financial instrument and selling it to investors including Dividing securities, Disbursement of funds and providing Credit rating:

· Led and supported the structuring, execution, and ongoing management of asset-backed securities(ABS) transactions, ensuring compliance with internal policies and external regulatory requirements.

· Used Python and Snowflake to store and analyze asset pools, including credit card receivables and auto loans, to ensure accurate representation and optimal structuring in securitization transactions.

· Ensured adherence to SEC regulations, risk management policies, and financial reporting standards throughout the securitization lifecycle, preparing regulatory filings and disclosures as required.

· Automated Securitization Process using Databricks, improving operational efficiency and reducing manual errors in deal execution and reporting.

· Developed dashboards using Tableau, QuickSight for portfolio analysis, to track performance and risk metrics of a diversified set of assets (stocks, bonds, mutual funds).

· Assisted in the ongoing administration of securitized deals, including monitoring performance, managing reporting, and addressing any issues related to loan performance or compliance.

Capital Markets: Developed an application to capture, analyze, and report risks for various asset classes traded by the client bank, including OTC bonds, derivatives, FX options, and commodities. Includes real-time risk analysis, scenario modelling, and VaR calculations.

· Created data pipelines to transfer data from AWS S3 buckets to Snowflake tables using Python and Databricks.

· Designed and developed real-time streaming pipelines to source data from IoT devices, optimizing data lakes, flow, retention, aggregation, and summarization for analytics performance.

· Built and published interactive Tableau dashboards for IP compliance, allowing users to monitor security positions daily.

· Conducted data quality checks and built analytical warehouses on Snowflake using Snow SQL.

· Experienced with AWS cloud services (EC2, S3, EMR, RDS, Athena) for data storage and processing.

· Developed automation scripts leveraging Python libraries to validate data accuracy before transferring to target databases.

· Performed data analytics on Capital One's DataLake using PySpark in the Databricks platform.

· Streamlined stress test regulatory reporting by creating an Excel and Python-based tracker for process management.

Marketing:

· Worked on the development and execution of multiple marketing campaigns (credit cards, loans, saving products), using both direct mail and email channels to drive customer acquisition and engagement.

· Utilized Salesforce Marketing Cloud for campaign execution, tracking, and analysis, and conducted A/B testing to optimize campaign performance.

· Performed campaign analysis on investment (ROI) for marketing campaigns promoting bank products (mortgages, credit cards, savings accounts) using campaign data and performance metrics using Excel, Python, Tableau.

· Performed A/B testing for email and online banking marketing campaigns, optimizing subject lines, call-to-actions, and design elements for personal loan and credit card promotions using SQL, Python, Google Optimize, Tableau.

· Leveraged Dun & Bradstreet (DNB) data to target new customer acquisitions, enhancing segmentation and driving high-quality leads.

· Developed a predictive lead scoring model to prioritize high-potential leads for personal loans, mortgages, and credit card offers, based on historical data and customer interactions using Python, SQL, Salesforce, Alteryx

· Built a predictive model to identify at-risk banking customers, using data such as transaction frequency, account balances, and product usage patterns, to reduce churn for checking and savings accounts using R, Python, Tableau, SQL

Small Business: Designed and developed multiple DataMart's to support marketing segmentation, product/channel incentives, and loan application tracking across Small Business, Home Equity, and Lending domains.

· Small Business Marketing: Designed and developed an analytically driven DataMart to support small business marketing segmentation driving increased engagement, profitability, and customer loyalty.

· BSML SB Data Infrastructure: Built a DataMart to optimize data sources for product and channel incentives, reporting, and analytics, improving frontline data accessibility.

· Lending Fact Base DataMart: Created a DataMart to integrate lending and deposit data, streamlining monthly customer summaries and providing integrated insights for loan and deposit applications.

Enterprise Metadata Management: Worked as a Senior Data Analyst in the Metadata Management Capability Architecture at Capital One, contributing to the implementation of a Centralized Metadata Strategy for a complex, heterogeneous data environment aimed at creating a robust framework for managing, sharing, and discovering metadata.

Responsibilities:

· Led requirements gathering sessions with business stakeholders to understand and document the needs for metadata management and reporting.

· Created source-to-target mapping documents and detailed business transformation rules to support data integration processes.

· Contributed to the automation of the ALLL (Allowance for Loan and Lease Losses) calculation process, ensuring efficient data flow and transformation.

· Performed data quality analysis using SnowSQL for building analytical data warehouses on Snowflake.

· Leveraged AWS cloud services (EC2, S3, EMR, RDS, Athena) for data processing and storage.

· Developed Python automation scripts to perform accuracy checks and ensure data consistency across various data sources and target databases.

· Performed data analytics on Capital One's DataLake using PySpark within the Databricksplatform.

· Streamlined stress test regulatory reporting by designing and automating a process tracker in Excel and Python, improving compliance reporting efficiency.

· Collaborated with the ETL team to support the upload process and ensure data integrity.

· Used SQL (Teradata, Snowflake, Oracle, SQL Server) for data validation, analysis, and reporting, including creating complex queries with derived tables, subqueries, and correlated queries.

· Engaged in data gap analysis, identified data quality issues, and implemented solutions to resolve discrepancies.

• Responsible for analyzing financial data and statistical loan risk analysis for a regional bank
• Worked on testing strategies, identifying potential risks, impacts and ultimately defining key success factors
• Conducted in-depth data analysis using Teradata SQL, flat files, and spreadsheets to extract insights and support decision-making
• Collaborated with business users, analysts, and technical teams to gather requirements, translate functional specifications into technical solutions, and develop reports to meet business needs
• Delivered ad-hoc data analysis to support management decisions by extracting and analyzing data from existing data warehouses
• Developed complex SQL queries for data extraction and built structured reports, enhancing business intelligence capabilities
• Designed and developed new reports using Business Objects/Crystal Reports on SQL Server
• Optimized SQL query performance using tools like Explain and query tuning techniques
• Utilized Teradata utilities (FastLoad, MultiLoad, and TPump) for efficient data loading and ETL processes
• Developed and executed BTEQ and FastExport scripts for data transformation and export tasks
• Created Teradata views, macros, and leveraged analytic functions to meet user reporting requirements
• Participated in data migration projects, successfully migrating data from legacy data warehouses (Oracle/DB2) to Teradata platforms
• Automated processes and optimized workflows using UNIX scripting
• Proficient in Teradata tools such as Teradata Manager, TDWM, PMON, DBQL, SQL Assistant, and BTEQ for performance monitoring and data management
• Worked with large-scale data warehouses (30-50 Terabytes) to handle complex data sets
• Experienced with ETL tools like Informatica and SAP BODS for efficient data integration and migration to Teradata
• Operated in Agile environments, collaborating in cross-functional teams to deliver data solutions