Nick Taylor Email and Phone Number

• Generative AI web app for technical accounting advisory (Python, Azure, Docker)

• Developed patent analytics datamart using USPTO API (Python)• Created natural language processing topic model for intellectual property trend and acquisition analysis (Python)• Built high-performance server for ETL and computation (Linux)

Data Science & Statistics• Built Reinforcement Learning trading algorithm (Snowflake, Azure, Python) (Ongoing)• Built Retrieval Augmented Generation (RAG) GenAI chat app (Azure AI Studio, Streamlit, Pinecone, Python)Business Intelligence• Advised client on business intelligence feature capabilities, vendor options, best practices, and potential development options• Implemented standards and processes for scalable enterprise reporting. • Developed suite of customized dashboards to support investment operations, performance attribution, portfolio management, and client servicing.

Data Science & Statistics• Developed use case presentation focused on data quality issues solvable using anomaly detection techniques (isolation forest, autoencoder)• Created plan outlining stages of model development (feature engineering, imputation, training, and cross-validation)• Engineered dataset from source data and parameterized script for random forest imputation.• Constructed two anomaly detection models for comparison: isolation forest and autoencoder neural net (SQL, Python, Databricks)Business Intelligence & Other• Developed Direct Lending cube to replace existing Excel dashboard (Python, Power BI, SQL)• Created metadata and data extraction scripts with Python• Power BI development, testing, and tuning (DAX, Power Query, data modeling)• Developed POCs and corresponding documentation for Microsoft Flows, Azure Data Factory, Python, and Power BI to test new features

Data Science• Built simulation for operations to project queueing, cycle times, and throughput, varying volume per month (Simio and Arena)• Built gradient boosted decision tree model in SQL Server ML Services (Python) to operationalize loan level payoff prediction• Developed unpaid principal balance forecast with linear regression (Excel)• Developed anomaly detection dashboard using an isolation forest model (R)• Built (ongoing) supervised model implementing ROSE (to address unbalanced dataset), and Penalized Logistic Model to identify potentially risky loans based on historical loan watch list (R)• Built support vector machine model to aid Credit and Underwriting with the task of classifying existing portfolio according to newly designed business line separation guidelines (R)Business Intelligence & Other• Scheduled distribution of reports (Python)• Developed operations dashboard to track units and borrowers processed/reprocessed by status over time (Power BI)• Developed market pricing and inventory indications cube and dashboard matching Zillow and Realtor.com data with internal portfolio (Power BI)• Created portfolio concentration dashboard with interactive MoM positive and negative variance drilldown by geography and borrower (Power BI)• Led data lineage project including planning, communication, reconstruction of datamart, software evaluation, and implementation• Developed and automated decks for Finance and Credit for monthly meeting with Goldman and quarterly meeting with Goldman and Advisory Council• Developed datamart for internal business logic and reconciliation• Provided reporting/analytical support to investment banking team leading up to purchase agreement by Goldman Sachs• Supported executives/consultants to achieve successful data integration with Goldman • Architected cube data warehouses, developed code to automate/reconcile• Prepared and reviewed key reporting to executives, investment bankers, and Oaktree Capital (investors)

Data Science & Statistics• Developed revenue forecast using step-wise regression analysis and interpolation from internally reported figures Business Intelligence & Other• Built macro to scrape tech business case files and aggregate into database, checked files to identify errors, coordinated with finance teams to gather commentary, and created slides for deck to present to Technology Investment and Strategy committee• Managed offshore staff accountants assigning tasks and reviewing work• Presented deck for 20 programs to explain financial performance • Researched/spoke to P&L revenue variances to budget, trend, and prior month at monthly close meetings• Enhanced reporting and drill down for $100M/year revenue program• Reduced offshore staff manual entry by 90% with automation• Automated/enhanced Excel templates for users and financial metrics for management using SQL, software, and VBA

Data Science & Statistics• Led integration of acquired company (CR Software) revenue accounting into parent.• Automated invoicing and revenue recognition within Oracle.• Software license, maintenance, and royalty revenue recognition and variance analysis.