Quantitative Research +1·Confirmed live in the last 24 hours·
Full-timePasadena, CA, USANo salary listedIn-person
About the Job
Requirements
Master’s or PhD in Financial Engineering, Quantitative Finance, or a related field.
Strong proficiency in Python for quantitative modeling.
Experience with numerical methods, optimization, and Monte Carlo simulations.
Knowledge of SQL and NoSQL databases and cloud platforms including Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
Familiarity with QuantLib, Pandas, NumPy, and SciPy.
Understanding of fixed income analytics, portfolio theory, and risk management.
Experience with Bloomberg, Refinitiv, FactSet, or similar market data tools.
Experience with vendor platforms such as Yield Book, Intex, or Aladdin.
Strong problem-solving and analytical thinking skills.
Excellent communication skills to explain complex quantitative concepts to non-technical stakeholders.
Responsibilities
Design, implement, and test quantitative models for quantitative analytics and risk.
Validate analytics model inputs and outputs against historical and computed data to ensure accuracy and robustness.
Acquire, clean, and analyze large-scale financial datasets from multiple sources.
Build data pipelines for real-time and batch processing of market and reference data.
Compute and analyze single-security risk metrics, including duration, convexity, spreads, key-rate durations, and key-rate convexities, to identify deviations or enhancements.
Support fixed income analytics and structured product modeling incorporating vendor-provided cash flows.
Work with traders, portfolio managers, and risk officers to interpret results and refine models.
Liaise with software development teams to integrate models into production systems.
Desired Qualifications
CFA, FRM, or CQF certification.
Financial Engineer Location – Pasadena, CA, (Onsite)
The ideal candidate will bridge the gap between finance and technology, leveraging mathematical modelling, data engineering, and programming expertise to solve complex financial problems. This role involves close collaboration with portfolio managers, risk teams, and software engineers to develop models that drive trading strategies, risk measurement, and financial decision-making.
EXPERIENCE AND REQUIRED SKILL SETS
Design, implement and test quantitative models for quantitative analytics and risk
Validate input and outputs for analytics models against historical and computed data to ensure accuracy and robustness.
Acquire, clean, and analyze large-scale financial datasets from multiple sources.
Build data pipelines for real-time and batch processing of market and reference data.
Compute and analyze singe security risk metrics (duration, convexity, spreads, krds, krcs) for any deviations or enhancements
Support fixed income analytics and structured product modelling incorporating cash flows from vendors.
Work with traders, portfolio managers, and risk officers to interpret results and refine models.
Liaise with software development teams to integrate models into production systems.
TECHNICAL SKILLS
Strong proficiency in Python for quantitative modelling.
Experience with numerical methods, optimization, and Monte Carlo simulations.
Knowledge of databases (SQL, NoSQL) and cloud platforms (AWS, Azure, GCP).
Familiarity with financial libraries (QuantLib, Pandas, NumPy, SciPy). FINANCE KNOWLEDGE • Understanding of fixed income analytics, portfolio theory, and risk management.
Experience with Bloomberg, Refinitiv, FactSet, or similar market data tools.
Experience working with vendor platforms like Yield book, Intex, Aladdin, etc. SOFT SKILLS • Strong problem-solving and analytical thinking.
Excellent communication skills to explain complex quantitative concepts to non-technical stakeholders.
Ability to work in a fast-paced, team-oriented environment.
FINANCE KNOWLEDGE
Understanding of fixed income analytics, portfolio theory, and risk management.
Experience with Bloomberg, Refinitiv, FactSet, or similar market data tools.
Experience working with vendor platforms like Yield book, Intex, Aladdin, etc.
SOFT SKILLS
Strong problem-solving and analytical thinking.
Excellent communication skills to explain complex quantitative concepts to non-technical stakeholders.
Ability to work in a fast-paced, team-oriented environment.
EDUCATION
Master’s or PhD in Financial Engineering, Quantitative Finance, or related field.