Quantitative Finance

Quantitative Finance Data Jobs

3 jobs found

1mo ago

Quantitative Data Engineer - Fixed Income and Mortgages

Selby Jennings New York, NY

New York, NY

1mo ago Closed

$350k - $450k/yr Full time 3d Design Tools Big Data Bigdata

This position is no longer accepting applications (closed Sep 17, 2026).

Job Description

This hands-on Quantitative Data Engineer role focuses on the end-to-end data workflow that supports loan-level and structured credit modeling. The position designs scalable pipelines and production-ready datasets used across quantitative investment and risk analytics.

Key Responsibilities

Design and maintain large-scale data pipelines for credit, mortgage, and structured product analytics.
Build and optimize loan-level feature engineering workflows and model input datasets.
Develop reproducible data processing frameworks for research, validation, and production deployment.
Partner with quantitative researchers to implement new features, validate methodologies, and improve model performance.
Collaborate with engineering teams to productionize research outputs while improving platform scalability and reliability.
Support ad hoc quantitative analysis and investigation of portfolio, collateral, and performance datasets.

Required Qualifications

Strong Python development experience, including production-quality code, testing, packaging, and code review practices.
Deep experience with distributed data processing using Spark and PySpark, including optimization of joins, partitioning, caching, skew management, and execution performance.
Advanced SQL skills, including experience querying large columnar data warehouses such as Snowflake, Redshift, BigQuery, Vertica, or similar platforms.
Experience building analytical datasets and feature engineering workflows for machine learning, statistical modeling, or quantitative research.
Strong understanding of reproducible data pipelines, experiment tracking, artifact management, and version-controlled development.
Experience in shared engineering environments using Git, automated testing, and CI/CD processes.
Ability to work directly with quantitative researchers and translate research requirements into scalable engineering solutions.

Technologies

Python
Spark, PySpark
SQL
Snowflake, Redshift, BigQuery, Vertica
Git
CI/CD

Preferred Qualifications

Experience working with loan-level, mortgage, consumer credit, or structured finance datasets.
Exposure to prepayment, default, transition, or loss modeling in credit or securitized products.
Familiarity with market and reference data providers, securitization cash flows, collateral reporting, or structured product analytics.
Experience with Databricks, Delta Lake, workflow orchestration tools, and modern cloud-based analytics platforms.
Exposure to model deployment, scoring frameworks, experiment tracking, or machine learning operations.
Experience with high-performance analytics tools such as Polars, DuckDB, Pandas, and scikit-learn.
Familiarity with workflow scheduling, data quality monitoring, and pipeline validation.
Comfort using AI-assisted development tools to accelerate coding, refactoring, testing, and codebase navigation.
Knowledge of cloud infrastructure, object storage, access controls, and cost-efficient data architecture.

Location

New York, NY (onsite)

Compensation

USD 350,000 - 450,000 per year

Education

Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Statistics, Financial Engineering, Mathematics, or Economic.

Additional Notes

Candidates from adjacent industries are welcome, particularly those with strong distributed computing, data engineering, and machine learning experience.

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1mo ago

Quantitative Data Scientist

Software Technology Inc Reston, VA

Reston, VA

1mo ago Closed

Full time Python Big Data Data Analysis

This position is no longer accepting applications (closed Aug 26, 2026).

Job Description

Quantitative Data Scientist role at Software Technology Inc in Reston, VA onsite, focusing on Python based modeling, risk analytics, and data engineering with AWS and big data tooling.

Responsibilities

Leverage advanced Python expertise across core libraries like NumPy, pandas, SciPy, statsmodels, scikit-learn, and QuantLib to design and maintain quantitative models.
Operate on large and complex mortgage and loan datasets with expert SQL skills to support analytics workflows.
Design, calibrate, and optimize Monte Carlo simulations and time series models used for risk assessment.
Apply counterparty credit risk concepts, including Potential Future Exposure methodologies, within modeling work.
Model interest rate dynamics, derivative pricing, and macro risk factor influences within analytical frameworks.
Develop and sustain data pipelines and analytics on AWS using S3, Lambda, Batch, Glue, EMR, CloudWatch, IAM, and EC2.
Adopt software engineering practices such as Git version control, unit testing, CI/CD pipelines, and shell scripting to ensure reliable deliverables.
Work with data lakes, NoSQL systems, and orchestration tools like Spark, Hive, and Airflow to enable scalable data processing.
Demonstrate strong analytical thinking and meticulous attention to detail across modeling tasks.
Communicate intricate technical concepts clearly to both technical and non-technical audiences.
Meet a minimum of five years of experience in quantitative modeling, data engineering, or related fields, with a Bachelor's degree as the educational baseline.

Requirements

Strong Python proficiency with libraries such as NumPy, pandas, SciPy, statsmodels, scikit-learn, and QuantLib.
Advanced SQL skills for handling large and complex mortgage or loan datasets.
Experience designing and optimizing Monte Carlo simulations and time-series models.
Solid understanding of counterparty credit risk, including Potential Future Exposure methodologies.
Familiarity with interest rate modeling, derivative pricing, and macro risk factor models.
Hands-on experience with AWS services including S3, Lambda, Batch, Glue, EMR, CloudWatch, IAM, and EC2.
Competence in software engineering practices such as Git, unit testing, CI/CD, and shell scripting.
Experience working with data lakes, NoSQL systems, and tools like Spark, Hive, and Airflow.
Strong analytical thinking and attention to detail.
Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
Minimum five years of experience in quantitative modeling, data engineering, or a related field, with a Bachelor's degree required.

Technologies

Python
NumPy
pandas
SciPy
statsmodels
scikit-learn
QuantLib
SQL
S3
Lambda
Batch
Glue
EMR
CloudWatch
IAM
EC2
Git
Spark
Airflow
NoSQL
Shell scripting
CI/CD

Skills

Business Analysis
Shell Script
SQL
NoSQL

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2mo ago

Senior Quantitative Data Engineer

Intone Networks Remote 🇺🇸 Remote

Remote

2mo ago Closed

Contract Python Senior Big Data

This position is no longer accepting applications (closed Aug 2, 2026).

Job Description

Intone Networks offers a remote contract opportunity for a Senior Quantitative Data Engineer. The role centers on designing and operating Python-first data pipelines and Snowflake data models that support structured finance analytics across multiple loan types. You will collaborate across 12 servicers to normalize and reconcile loan-level data spanning whole loans, asset-backed securities (ABS), HELOCs, RVs, student loans, and other esoterics. This position emphasizes scalable data architectures, automated data quality, and an AI-enabled analytics trajectory, including a dashboard layer to replace legacy Tableau workflows.

Responsibilities

Own end-to-end Python-first data pipelines across 12 servicers, normalizing and reconciling loan-level data across whole loans, ABS, HELOCs, RVs, student loans, and esoterics.
Build Snowflake data models to support structured finance analytics.
Lead LMS migration reconciliation.
Develop automated data quality frameworks.
Contribute to an AI-native dashboard layer replacing legacy Tableau workflows.

Requirements

7–10 years in financial services data platforms
Structured finance domain knowledge (ABS, HELOCs, whole loans, etc.)
Expert Python — Polars, Spark, Pandas
Advanced Snowflake (modeling + optimization)
High-volume reconciliation in production environments

Technologies

Python
Snowflake
Polars
Spark
Pandas
Azure Data Factory
Plotly/Dash
Tableau

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Quantitative Finance Data Jobs

Quantitative Data Engineer - Fixed Income and Mortgages

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