Data Scientist · Applied ML & Analytics

Production ML and analytics for retail banking operations.

Data scientist with 19 years in retail banking. I build production ML, SQL/Python pipelines, and Tableau dashboards that help teams monitor performance, prioritize work, and make better decisions. Android apps in my spare time.

19years in banking and analytics
Top 3enterprise modeling competition, two years running
2shipped Android apps in the public store

Selected work

Public-data analytics and ML projects that show how I move from raw data to useful decisions.

Outside the day job

Two native Android apps shipped on my own time.

Selected roles

The short version of the story behind the resume.

Data Scientist, AVP

PNC Financial Services
2025 — Present
  • Built an XGBoost workflow that identifies operational errors 10x more often than random sampling, taken through validation, production deployment, and Tableau monitoring.
  • Built the case-sampling tool QA reviewers use day to day; model scores drive risk-targeted review with a random control sample for ongoing validation.
  • Build Tableau dashboards leadership uses to track operational trends, risk patterns, and team performance.

Sr. Business Analytics Consultant, AVP

PNC Financial Services
2022 — 2025
  • Owned analytics for relationship-operations strategy, supporting decisions for line-of-business leaders.
  • Built SQL, PySpark, and Hive pipelines on Cloudera, orchestrated with Oozie, that fed downstream reporting and modeling work.
  • Top 3, two years running, in PNC's enterprise data science competition: multi-class LightGBM (2024), Cox proportional hazards survival model (2025).

Business Analytics Consultant and earlier roles

PNC Financial Services
2017 — 2022 and prior
  • Built the first analytics function on multiple teams that previously had none.
  • Replaced legacy Excel/VBA reporting with Python and SQL pipelines.
  • Grew from reporting and collections roles into full analytics ownership.

Core stack

Tools and methods I use to move from raw data to business decisions.

Languages and platforms

PythonSQLPySparkHadoopSparkHiveClouderaTeradataOracleOozieJupyterGitHubCloudflare Workers

Modeling and analytics

XGBoostLightGBMScikit-learnPandasNumPyCox Proportional HazardsSurvival AnalysisClassificationFeature EngineeringStatistical SamplingA/B TestingNLP (TF-IDF)LLMs

Visualization

TableaumatplotlibseabornExcelExecutive Dashboards

Let's connect.

Always up for a conversation about data science, analytics engineering, business intelligence, or product work. Reach out anytime.