Hybrid Quant Analytics Engineer - Market Risk & Python

Next Level Business Services Inc.; Jersey City (NJ); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Next Level Business Services Inc. in Jersey City is seeking a Quant Analytics professional specializing in Python to tackle market risk analytics and related financial modeling tasks.

This hybrid role focuses on building analytical solutions for complex risk use cases. Ideal candidates will have hands-on Python development experience, familiarity with P&L calculations and risk metrics, and a track record of processing large-scale financial datasets.

Qualifications

• Hands-on Python development for analytical solutions.
• Background in Market Risk Analytics and P&L concepts.
• Experience with large-scale financial datasets and complex transformations.
• Focus on pricing analytics, risk analytics or financial modeling.
• Ability to optimize data pipelines handling billions of records.
• Experience in global banking or capital markets preferred.
• Strong collaboration with Quant teams and business stakeholders.

Responsibilities

• Develop analytical solutions for market risk use cases using Python.
• Collaborate with Quant teams and stakeholders to implement pricing and risk analytics.
• Handle large-scale datasets and optimize data pipelines for performance and scalability.
• Contribute to financial modeling and analytics environments.

Skills

Python development

Market risk analytics

P&L calculations

P&L vectors

risk metrics

quantitative data processing

data analysis

communication

problem solving

Tools

Distributed computing

Grid computing platforms

Job description

Next Level Business Services Inc. in Jersey City is seeking a Quant Analytics professional specializing in Python to tackle market risk analytics and related financial modeling tasks.

This hybrid role focuses on building analytical solutions for complex risk use cases. Ideal candidates will have hands-on Python development experience, familiarity with P&L calculations and risk metrics, and a track record of processing large-scale financial datasets.