Freelance AI/ML consulting
Machine-learning systems designed around evidence, governance, and review
I work as an AI/ML Research Consultant on projects that require more than a standalone predictive model: clear data contracts, reproducible evaluation, provenance, explainability, and review mechanisms are treated as part of the system design.
Selected engagement · 2026–present
InvestMint — governed semantic banking and forecasting
My work for InvestMint focuses on the design of a governed analytical layer for financial and operational data. Publicly describable contributions include:
Defining synthetic and canonical data contracts that separate source-specific inputs from stable analytical interfaces.
Designing forecasting evaluation gates and business-baseline comparisons.
Adding provenance, audit, and review semantics around model outputs.
Integrating explainability hooks and human-in-the-loop review paths.
Building reproducible Python prototypes and FastAPI-style interface contracts.
Creating test fixtures that allow client-facing workflows to be validated without exposing confidential data.
Technical scope
Tools and system concerns
- Python
- pandas
- scikit-learn
- time-series evaluation
- explainable AI
- data contracts
- provenance
- FastAPI
- testing
- human-in-the-loop systems