Data Scientist | AI Engineering, Machine Learning & Data Analytics
I work on customer growth, forecasting, reporting and AI workflows that help teams decide what to do next. I start with the business problem, build the model or workflow, and make the result useful to the people making the decision.
Open to remote US full-time W2 and contract roles in data science, AI engineering, data analytics and data-focused technical program management.
- Customer acquisition, churn, lifetime value and campaign measurement.
- Explainable Boosting Machines, XGBoost, Random Forest, clustering and forecasting.
- LLM applications, prompt and context engineering, semantic layers, MCP tools and evaluations.
- Python, SQL, Spark, Azure, Databricks, Snowflake, Microsoft Fabric, Power BI and Tableau.
These public projects are separate from my professional work. Their descriptions reflect the source code, not verified commercial deployment or measured business results.
Product research can become disconnected searches and notes. This Python application combines trend discovery, specialist LLM analysis and a human review queue, bringing research and approval into one workflow.
FastAPI, Celery, Redis, PostgreSQL and Docker. Marketplace publishing currently includes demonstration placeholders; the monitoring and repair workflow is experimental.
Income, bills, assets and spending are easier to understand in one view. This budgeting and net-worth application combines account tracking with scheduled LLM summaries that highlight changes and possible next steps.
React, Express, SQLite and Groq, with scheduled analysis and saved insight history.
- Loan repayment classification: a Keras notebook modeling fully paid versus charged-off loans, not loan approval decisions.
- Movie recommendations: a content-based learning notebook using RAKE keywords, CountVectorizer and cosine similarity.
- PubMed research toolkit: older Python search, metadata and retry/resume collection scripts. The legacy downloader needs modernization before use with current PMC access policies.
- Generative AI Professional Certificate by Snowflake (Snowflake, October 2026).
- Data Engineering Professional Certificate by Snowflake (Snowflake, October 2026).
- LinkedIn Learning Professional Certificate: Impacting the Business as a Senior Manager or Leader (LinkedIn, October 2026).
- Production-Ready AI Engineering (LinkedIn, October 2026).
- AI Evaluations: Foundations and Practical Examples (LinkedIn, October 2026).
- Building AI Agents with Snowflake (LinkedIn, October 2026).
- Advanced Data Engineering with Snowflake (LinkedIn, October 2026).
- Build with AI: Production-Ready AI Agent Systems on Databricks (LinkedIn, September 2026).
- MLOps with Databricks (LinkedIn, September 2026).
- Managing and Scaling Power BI Semantic Models with MCP Server (LinkedIn, September 2026).
- Advanced Snowflake: Deep Dive Cloud Data Warehousing and Analytics (LinkedIn, September 2026).
View the full catalog of 45 certificates.
These course titles describe completed learning, not production-readiness claims for the projects above.