Risk Management Developer/ Data Analytics

RedStream Technology; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

RedStream Technology in New York is seeking a developer/data analytics engineer to support risk analysis and maintain an existing risk analytics platform focused on structured credit and loan portfolio analysis. You will build tools for valuation, scenario analysis, Monte Carlo simulations, data processing, model execution, reporting and visualization.

The role requires collaboration with business users and quantitative concepts, but you are not expected to design financial models; ownership of

Qualifications

• Bachelor's or master's degree or equivalent in a technical field.
• Experience with Pandas/Polars for data analysis.
• Experience with SQL and relational databases (MySQL preferred).
• Experience automating analytical workflows.
• Experience with performance optimization or parallel processing.
• Ownership of an existing codebase and extending it reliably.

Responsibilities

• Maintain and enhance existing risk analytics applications and workflows.
• Develop tools for model execution, data collection, validation, and analysis.
• Build and improve applications for default analysis, rating transitions, prepayments analysis, regression analysis, and reporting.
• Work with loan-level and transaction-level time series data from raw sources through normalization.
• Improve performance, reliability, logging, auditability, and usability of analytical processes.
• Collaborate with Risk Management and IT to deliver practical tools for research, valuation, and portfolio analysis.

Skills

Python

Pandas/Polars

SQL

Education

Bachelor's or Master's in CS/Math/Stats/Engineering

Tools

MySQL

FastAPI

React

Apache ECharts

Docker

Job description

NYC/ Onsite

Perm role

The Risk Management Group is seeking a developer/data analytics engineer to provide daily support to the team regarding risk analysis/monitoring, and to maintain and extend an existing risk analytics platform supporting structured credit, loan portfolio analysis, and related investment decision-making.

The role involves developing tools for valuation, scenario analysis, Monte Carlo simulations, data processing and analysis, model execution, reporting, and visualization.

The candidate should be comfortable working with quantitative risk concepts and collaborating directly with business users, but is not expected to design financial models.

Responsibilities:

• Maintain and enhance existing risk analytics applications and workflows.
• Develop tools for model execution, data collection, validation, and analysis.
• Build and improve applications for default analysis, rating transition matrices, prepayments analysis, regression analysis, and probability/exceedance curve reporting.
• Work with loan-level and transaction-level time series data from raw source formats through normalized datasets.
• Improve performance, reliability, logging, auditability, and usability of analytical processes.
• Collaborate with Risk Management and IT teams to deliver practical tools for research, valuation, and portfolio analysis.

Qualifications:

• Bachelor's or master's degree in computer science, mathematics, statistics, engineering, data science, financial engineering, quantitative finance, or a related technical field.
• Experience with data analysis libraries such as Pandas and/or Polars.
• Experience with SQL and relational databases, preferably MySQL.
• Experience automating analytical workflows, including Excel-based processes.
• Experience with performance optimization, multiprocessing, parallel processing, or job orchestration.
• Ability to take ownership of an existing codebase and extend it in a reliable, maintainable way.
• Working knowledge of quantitative concepts such as Monte Carlo simulation, probability distributions, regression analysis, percentiles, default rates, and transition matrices.

Preferred Qualifications:

• Experience developing financial, risk, investment, or analytics applications.
• Experience with FastAPI or similar Python web frameworks.
• Experience with React and charting libraries such as Apache ECharts or Recharts.
• Experience with Docker or containerized deployment.
• Familiarity with Excel/VBA integration, Jupyter notebooks, PyTorch is a plus where relevant.
• Familiarity with structured credit transactions, securitization, consumer/corporate loan data is a plus.