Quantitative Analytics

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

Job Role: Quant Analytics with Python (Market Risk)

Location: Jersey City, NJ (Hybrid)

Job Type: Full-time permanent role

Job Description:

• Strong hands-on experience in Python development with the ability to build analytical solutions for complex quantitative and market risk use cases.
• Experience or background in Market Risk Analytics in a plus, including understanding of P&L calculations, P&L vectors, risk metrics, and quantitative data processing.
• Experience working with large-scale financial datasets and performing complex aggregations, transformations, and analytics on high-volume data.
• Candidate will focus on developing solutions for pricing analytics, risk analytics, trade analytics, or financial modeling environments.
• Ability to process and optimize data pipelines handling billions of records, with a focus on performance, scalability, and efficiency.
• Experience working within global banking or capital markets organizations and handling enterprise-scale financial datasets.
• Preference for candidates who combine strong quantitative/domain knowledge with technical development skills, rather than purely application development experience.
• Preference for candidate who has experience solving real-world analytical problems involving vector calculations, complex aggregations, and quantitative data modeling.
• Familiarity with distributed computing/grid computing platforms and running large-scale analytics workloads is a plus.
• Ability to collaborate effectively with Quant teams and business stakeholders.
• Strong communication and problem-solving skills.