- Company Name
- BeaconFire Inc.
- Job Title
- Python Risk Model Developer
- Job Description
-
**Job Title**
Python Risk Model Developer
**Role Summary**
Develop, validate, and deploy quantitative risk models using Python/R for regulatory stress testing and enterprise risk management. Collaborate cross‑functionally to design workflow pipelines, monitor model performance, and communicate results through analytical visualizations.
**Expectations**
- Long‑term contract position focused on model development, implementation, and ongoing performance monitoring.
- Work closely with risk, finance, and IT stakeholders to meet project timelines and deliverables.
- Apply statistical tests and machine learning techniques to improve model accuracy and robustness.
**Key Responsibilities**
1. Design and build Python/R models for Balance Sheet, Fee Revenues, Macro‑economic, and Expense forecasts.
2. Develop execution workflows that calculate risk metrics under stress scenarios, sensitivity, and attribution analyses.
3. Coordinate coding, testing, implementation, and documentation of financial models with functional teams.
4. Create processes and tools to monitor model performance and validate results against statistical benchmarks.
5. Produce presentation decks and visual analytics using JupyterHub/Python for stakeholder communication.
6. Apply data mining, data modeling, and machine learning to large financial datasets to enhance model performance.
**Required Skills**
- Proficiency in Python and/or R; experience with Pandas, SQL, and data manipulation.
- Strong programming in additional languages (C++, Java, MATLAB) is a plus.
- Advanced knowledge of statistical techniques: regression, time‑series analysis, hypothesis testing.
- Experience with ML methods applicable to risk modeling (e.g., supervised learning, feature engineering).
- Ability to document code, build documentation, and prepare presentation materials.
- Excellent verbal and written communication for cross‑team coordination.
**Required Education & Certifications**
- Master’s, MBA, or PhD in Quantitative Field (Computer Science, Financial Engineering, Mathematics, Data Science, or Engineering).
- Relevant professional certifications (e.g., FRM, PRM, CFA) are an advantage but not mandatory.
Pittsburgh, United states
On site
03-12-2025