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Responsible for accounts payable functions including invoice processing, vendor payments, reconciliations, and maintaining payable records to support accurate financial reporting.

Lead risk management and credit/fraud strategy; build end-to-end risk models for unsecured portfolios; perform feature engineering with credit bureau data; manage a team; run programs; create executive-level presentations and data dashboards using analytics and visualization tools.

No responsibilities were provided in the job description.

Design, build and validate credit risk scorecards (application, behavioral, collections). Extract, clean, and preprocess data using SQL; develop ML models in Python. Monitor model performance, backtest and recalibrate to meet regulatory standards. Collaborate with business teams and document modeling processes for governance and audit.

Lead actuarial pricing and risk monitoring activities for P&C products, including data extraction, profitability and trend analysis, rate development, filings support, predictive modeling (GLMs, XGBoost, Lasso), QC, automation proposals, and cross-functional collaboration to inform underwriting and pricing decisions.

No responsibilities provided. Title indicates a developer role working with Microsoft Power Platform (Power Apps, Power Automate) to build low-code business solutions.

Respond to basic accounts payable inquiries, handle and resolve AP issues, and perform basic troubleshooting for AP processes.

Design, build, and deploy scalable full‑stack applications using Python backends (Flask/FastAPI/Django) and React frontends. Develop cloud‑native solutions on GCP (Cloud Run, BigQuery, Pub/Sub, Vertex AI, Cloud Functions), integrate AI/ML models, optimize performance/security, implement CI/CD, testing, and monitoring, and work with relational and NoSQL databases.

Design and implement data models, reverse-engineer physical data models from databases/SQL, resolve system integration challenges, support data architecture decisions including data movement and technology strategy.

Lead data engineering strategy across projects and teams, drive innovation and model optimization, represent the team in executive meetings, and develop long-term data engineering and infrastructure plans.