Lorven Technologies Inc.

Python Risk Model Developer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Python Risk Model Developer in Pittsburgh, PA, on a contract basis. Requires a Master’s/PhD in a quantitative field, proficiency in Python/R, SQL, and advanced statistical techniques, with relevant industry experience.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
January 14, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Pennsylvania, United States
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🧠 - Skills detailed
#Matlab #ML (Machine Learning) #Regression #Data Science #Pandas #C++ #SQL (Structured Query Language) #Python #R #Documentation #Jupyter #Programming #Datasets #Mathematics #Data Mining #Time Series #Java #Computer Science
Role description
Hi , We are looking out for the professionals for the below position. If you are interested in below role to apply, please give a quick response here. Position: Python Risk Model Developer Location: Pittsburgh, PA Duration: Contract Job Description: Key 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. Qualifications: • 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.)"