Quantitative Developer
💼 SVP – Quantitative Model Implementation Expert (W2 only)
📍 Remote (CST/EST preferred), Irving, TX
🏦 Client: Leading Banking/Financial Services Firm
🕒 Contract | W2 | Must have financial services domain experience
Are you passionate about model implementation and want to make a direct impact in a collaborative, high-caliber quantitative modeling team? We're hiring a Quantitative Model Implementation Expert to join a group of model developers working on scalable, efficient, and standardized implementation of new economic models.
SVP – Quantitative model
Team of 26 model developers
New model implementation
Looking for someone with Model implementation
Experience with Quantitative model
Strong python programming skills
Implementing models
What think should be hard coded, basically someone who can review the codes of the team
CST or EST time zone Irving Texas
Not require phd in macroeconomics, graduate degree is required.
Ideal candidate is a Economist, model implementation is highly preferred.
Interview process for both roles will be 1 interview panel for an hour.
Mostly regression models, management of fairly simply models.
Using pandas and NumPy in simple ways or standardized models
🧠 What You’ll Do:
Design and enforce best practices in model implementation
Build standardized libraries and modular functions/classes to simplify modeling
Implement and maintain a series of interconnected regression and time-series models
Conduct code reviews and provide guidance to junior developers to ensure clean, maintainable, and scalable code
Optimize Python-based model performance using Pandas, NumPy, and related tools
Help determine what aspects of models should be hard-coded for performance and maintainability
✅ What We’re Looking For:
7+ years of model implementation experience (post-Master’s) in a financial institution
Strong foundation in econometrics, particularly OLS and time-series models
Expert-level Python programming and experience building production-grade code
Previous experience managing interconnected models and implementing models with modular code
Knowledge of economic concepts — ideal candidate has an economics background
Hands-on experience with code review, version control, and collaborative team environments
Strong communicator and detail-oriented problem solver
Familiarity with model governance is a plus
🎓 Education:
Graduate degree required (Master’s in Economics, Quantitative Finance, Statistics, or related field)
PhD not required, but a plus
📝 Interview Process:
1 interview panel (1 hour total)
💡 This is an excellent opportunity for someone who loves bridging quantitative modeling and clean implementation — especially those looking to grow into a technical leadership role within a dynamic financial environment.
📩 Please share me your updated resume to discuss this further.
💼 SVP – Quantitative Model Implementation Expert (W2 only)
📍 Remote (CST/EST preferred), Irving, TX
🏦 Client: Leading Banking/Financial Services Firm
🕒 Contract | W2 | Must have financial services domain experience
Are you passionate about model implementation and want to make a direct impact in a collaborative, high-caliber quantitative modeling team? We're hiring a Quantitative Model Implementation Expert to join a group of model developers working on scalable, efficient, and standardized implementation of new economic models.
SVP – Quantitative model
Team of 26 model developers
New model implementation
Looking for someone with Model implementation
Experience with Quantitative model
Strong python programming skills
Implementing models
What think should be hard coded, basically someone who can review the codes of the team
CST or EST time zone Irving Texas
Not require phd in macroeconomics, graduate degree is required.
Ideal candidate is a Economist, model implementation is highly preferred.
Interview process for both roles will be 1 interview panel for an hour.
Mostly regression models, management of fairly simply models.
Using pandas and NumPy in simple ways or standardized models
🧠 What You’ll Do:
Design and enforce best practices in model implementation
Build standardized libraries and modular functions/classes to simplify modeling
Implement and maintain a series of interconnected regression and time-series models
Conduct code reviews and provide guidance to junior developers to ensure clean, maintainable, and scalable code
Optimize Python-based model performance using Pandas, NumPy, and related tools
Help determine what aspects of models should be hard-coded for performance and maintainability
✅ What We’re Looking For:
7+ years of model implementation experience (post-Master’s) in a financial institution
Strong foundation in econometrics, particularly OLS and time-series models
Expert-level Python programming and experience building production-grade code
Previous experience managing interconnected models and implementing models with modular code
Knowledge of economic concepts — ideal candidate has an economics background
Hands-on experience with code review, version control, and collaborative team environments
Strong communicator and detail-oriented problem solver
Familiarity with model governance is a plus
🎓 Education:
Graduate degree required (Master’s in Economics, Quantitative Finance, Statistics, or related field)
PhD not required, but a plus
📝 Interview Process:
1 interview panel (1 hour total)
💡 This is an excellent opportunity for someone who loves bridging quantitative modeling and clean implementation — especially those looking to grow into a technical leadership role within a dynamic financial environment.
📩 Please share me your updated resume to discuss this further.
