Cynet Systems ยท 16 hours ago
Python Risk Model Developer
Cynet Systems is seeking a Python Risk Model Developer to collaborate with stakeholders and develop risk models for regulatory stress testing and risk management. The role involves designing workflows, coordinating implementations, and applying statistical methods to enhance model performance.
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Responsibilities
Collaborate with stakeholders throughout the organization to develop project plans of delivering objects and timelines of model development and implementation
Develop risk models in Python/R used by risk teams for regulatory stress testing submission and company risk management. Design and build the execution workflow of models to forecast Balance Sheet, Fee Revenues, Macroeconomic Factors, Expense and calculate risk metrics under various stress scenarios, sensitivity & attribution analysis
Coordinate with different functional teams to implement models and coordinate coding, testing, implementation and documentation of financial models
Develop processes and tools to monitor and analyze model performance to ensure the expected application performance levels are achieved. Also, apply various statistical and analytical tests for validating models and results
Develop presentation decks using visual analytics tools and techniques. (JupyterHub/Python)
Apply data mining, data modelling and machine learning techniques to analyze large financial datasets and enhance the model performance
Qualification
Required
Master/MBA/PhD's Degree in a quantitative field (computer science, financial engineering, mathematics, data science or engineering)
Experience using one or more programming languages (Python, R, C++, Java, Matlab, etc.) and manipulating data using SQL and Pandas
Excellent written and verbal communication skills for coordination across teams
Understanding of design, development and implementation of mathematical, financial risk and ML models
Relevant work experience in a related field based on education level
Knowledge of advanced statistical techniques and concepts (regression, time series analysis, statistical tests, etc.)