This role pays less than
75%
of similar roles. Most pay
$147,425–$216,250
— the shaded band above.
At the midpoint, this role pays about
$148k
versus about
$182k
for comparable roles.
Based on 240 similar postings.
Employer
About Goldman Sachs
Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.
Goldman Sachs currently has
142 open roles
on FindRole.
Listed pay typically runs
$137,000–$250,000
across 57 roles with salary data.
The Core Engineering, FTP Strats, Associate, Quantitative Engineering joins the Funds Transfer Pricing team within Corporate Treasury to develop robust quantitative Asset Liability Management models and frameworks. This role involves designing and implementing mathematical models to price funding for assets and liabilities, developing fixed-income tradable models for risk centralization, and creating pricing models for deposits to quantify market sensitivities. The individual will manage the end-to-end systems development cycle, including requirements analysis, coding, testing, and post-go-live maintenance while providing analytics and reporting to ensure transparency on funding transfers. Candidates must possess an advanced degree in a quantitative field or a bachelor’s with relevant experience, proficiency in Python or similar programming languages, and strong communication skills to bridge technical and business audiences. The work focuses on optimizing liquidity, managing risk, and aligning desk decision-making with firm financial objectives.
Design and implement quantitative frameworks and mathematical models to price funding for assets and liabilities.
Develop fixed-income tradable models for internal funding transfer and risk centralization.
Create pricing models for deposits to quantify market sensitivity and interest rate risks.
Identify business needs and data requirements to develop necessary process workflows and engineering solutions.
Develop analytics and reporting tools to provide transparency on FTP and ALM.
Translate complex model outputs into understandable results for non-technical clients.
Manage the end-to-end systems development cycle including coding, testing, and post-go-live maintenance.
What we're looking for
Advanced degrees (PhD or Masters) in a quantitative field such as Mathematics, Physics, Engineering, or Computer Science, or a bachelor’s with relevant work experience.
Strong analytical and problem-solving ability.
Proficiency in Python or a similar programming language.
Excellent communication skills to engage both technical and business audiences globally.
Familiarity with financial markets, financial products, and optimization (preferred).
Ability to manage the end-to-end systems development cycle from requirements analysis through post-go-live maintenance.
Python
C++
R
Machine Learning
Time-Series Analysis
Monte Carlo Simulation
Conformal Prediction
Feature Engineering
Model Risk Management
Econometrics
Statistical Learning
Hyperparameter Tuning
Exploratory Data Analysis
Remote (San Francisco, CA)+23 days ago
$138,905–$285,982
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