Financial Engineer – Quantitative Analytics & Risk

Financial Engineer – Quantitative Analytics & Risk

Los Angeles, CA

Full time with gemini Solutions

Role Overview

We are seeking a Financial Engineer to work at the intersection of Quantitative Analytics,

Risk Management and Technology. The role will involve working closely with Quant teams,

Risk Managers, Portfolio Managers and Technology teams to build solutions, wrappers,

services and integrations around quantitative models and analytics.

The ideal candidate combines strong financial markets and risk knowledge with hands-on

programming and analytical skills, and is comfortable explaining quantitative results and

investigating differences in risk and attribution numbers.

Key Responsibilities

Work with Quant, Risk and Investment teams to understand quantitative models,

analytics and business requirements.

Support Fixed Income and structured-product analytics, including pricing, risk and

cash-flow analytics.

Build wrappers, services, APIs and integrations around quantitative/risk models and

analytical platforms.

Analyze and explain changes or differences in risk, performance and attribution

results.

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

Investigate breaks across positions, market data, reference data, cash flows, model

inputs and analytics.

Develop functional and statistical data/analytics validation checks and support root

cause analysis.

Collaborate with engineering teams to productionize quantitative solutions and data

pipelines.

Required Skills & Experience

5+ years in Financial Engineering, Quantitative Analytics, Risk Analytics, FES,

Quant Development or Investment Analytics.

Strong experience working directly with Quant teams, Risk Managers and/or Portfolio

Managers.

Strong Python and SQL skills; experience building production-quality analytical

solutions.

Strong understanding of Fixed Income and risk analytics

Ability to understand why risk or attribution numbers change and explain the drivers

to business stakeholders.

Understanding of the trade lifecycle through risk and attribution.

Strongly Preferred

Hands-on experience with Mortgage / MBS, ABS, Credit or other structured products.

Experience with mortgage/ABS cash flows, prepayment, default and embedded

optionality.

Experience working in an FES / Quantitative Analytics environment supporting

institutional investment or risk teams.

Knowledge of QuantLib, NumPy, Pandas, SciPy, APIs and financial data pipelines