Home › Companies › Hdpc Fa Us2 Oraclecloud Com CX 3002 › Engineering - Dallas - Vice President, Quantitative Engineering - 049460
Engineering - Dallas - Vice President, Quantitative Engineering - 049460
Hdpc Fa Us2 Oraclecloud Com CX 3002 · Dallas, TX, United States · Active · Oracle Recruiting Cloud / Fusion HCM
Job facts
| Field | Value |
|---|---|
| Company | Hdpc Fa Us2 Oraclecloud Com CX 3002 |
| Title | Engineering - Dallas - Vice President, Quantitative Engineering - 049460 |
| Normalized title | - |
| Department / team | Vice President |
| Location | Dallas, TX, United States |
| Work model | - |
| Employment type | - |
| Salary | - |
| Status | active |
| ATS provider | Oracle Recruiting Cloud / Fusion HCM |
| Posted / first seen | 2026-06-03 / 2026-06-04 |
| Changed / last seen | 2026-06-04 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Hdpc Fa Us2 Oraclecloud Com CX 3002. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Oracle Recruiting Cloud / Fusion HCM. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in Dallas. | Open |
| Department jobs | Active postings in Vice President. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Hdpc Fa Us2 Oraclecloud Com CX 3002 |
| Source | 6c2fc4b4-b977-4fca-ad16-3207bde507b7 |
| ATS provider | Oracle Recruiting Cloud / Fusion HCM |
Description
Description
Job Duties: Vice President, Quantitative Engineering with Goldman Sachs & Co. LLC in Dallas, Texas. Multiple positions available. Lead the development, implementation, and documentation of scenarios comprised of a broad range of economic and financial variables for businesses within the Firm. Collaborate with internal stakeholders, analyzing user needs from a scenario design perspective and addressing data, model, and implementation issues. Analyze large data sets (structured and unstructured) to build predictive models of business-relevant market variables. Develop, refine, and improve scenarios by leveraging knowledge in financial markets, economics, current events, statistical analysis, and programming. Build and challenge risk models, identify and quantify vulnerabilities across market, credit, liquidity risk and modeling. Create and maintain clear and complete technical documentation of the risk-model performance testing approach and process. Mentor junior and mid-level team members.
Job Requirements: Master’s degree (U.S. or foreign equivalent) in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research, or related quantitative field and three (3) years of experience in job offered or a related quantitative engineering role OR Bachelor’s degree (U.S. or foreign equivalent) in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research, or related quantitative field and five (5) years of experience in job offered or a related quantitative engineering role OR PhD degree (U.S. or foreign equivalent) in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research, or related quantitative field and one (1) year of experience in job offered or a related quantitative engineering role. Prior experience must include three (3) years of experience (with a Master’s degree) OR five (5) years of experience (with a Bachelor’s degree) OR one (1) year of experience (with a PhD degree) with 5 of the 8 following skills: C++, Java, or Python; performing financial mathematics, including at least one of the following: stochastic calculus, no-arbitrage pricing theory, multivariable calculus, linear algebra, probability theory, numerical methods, or Monte-Carlo techniques; performing analysis leveraging market risk, credit risk, liquidity risk, or mathematical finance concepts; object-oriented programming and scripting programming languages such as Python or Java; implementing mathematical models or analytics in production-quality software; working with database query languages, such as SQL, MongoDB, or other data management tools to process large datasets; applying algorithms or data structures to write complex programs; and developing pricing models for financial products to model risk, economics, and cash flows under normal and distressed market environments.
©The Goldman Sachs Group, Inc., 2026. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law.
Full job record
| Job ID | 748f6b90b6f109efd9c83b68d578a32e05d5bc53 |
| Org ID | be11fab8-3f8a-45d7-b0b8-f801e8cc9e3b |
| Source ID | 6c2fc4b4-b977-4fca-ad16-3207bde507b7 |
| Board ID | 6c2fc4b4-b977-4fca-ad16-3207bde507b7 |
| Provider | oracle_hcm |
| Provider Job Key | 175521 |
| Title | Engineering - Dallas - Vice President, Quantitative Engineering - 049460 |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Dallas, TX, United States |
| Department | Vice President |
| Team | — |
| Employment Type | — |
| Workplace Type | — |
| Remote Policy | — |
| Country | United States |
| Region | TX |
| City | Dallas |
| Salary Raw | Description Job Duties: Vice President, Quantitative Engineering with Goldman Sachs & Co. LLC in Dallas, Texas. Multiple positions available. Lead the development, implementation, and documentation of scenarios comprised of a broad range of economic and financial variables for businesses within the Firm. Collaborate with internal stakeholders, analyzing user needs from a scenario design perspective and addressing data, model, and implementation issues. Analyze large data sets (structured and unstructured) to build predictive models of business-relevant market variables. Develop, refine, and improve scenarios by leveraging knowledge in financial markets, economics, current events, statistical analysis, and programming. Build and challenge risk models, identify and quantify vulnerabilities across market, credit, liquidity risk and modeling. Create and maintain clear and complete technical documentation of the risk-model performance testing approach and process. Mentor junior and mid-level team members. Job Requirements: Master’s degree (U.S. or foreign equivalent) in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research, or related quantitative field and three (3) years of experience in job offered or a related quantitative engineering role OR Bachelor’s degree (U.S. or foreign equivalent) in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research, or related quantitative field and five (5) years of experience in job offered or a related quantitative engineering role OR PhD degree (U.S. or foreign equivalent) in Computer Science, Financial Engineering, Applied Mathematics, Data Science, Operations Research, or related quantitative field and one (1) year of experience in job offered or a related quantitative engineering role. Prior experience must include three (3) years of experience (with a Master’s degree) OR five (5) years of experience (with a Bachelor’s degree) OR one (1) year of experience (with a PhD degree) with 5 of the 8 following skills: C++, Java, or Python; performing financial mathematics, including at least one of the following: stochastic calculus, no-arbitrage pricing theory, multivariable calculus, linear algebra, probability theory, numerical methods, or Monte-Carlo techniques; performing analysis leveraging market risk, credit risk, liquidity risk, or mathematical finance concepts; object-oriented programming and scripting programming languages such as Python or Java; implementing mathematical models or analytics in production-quality software; working with database query languages, such as SQL, MongoDB, or other data management tools to process large datasets; applying algorithms or data structures to write complex programs; and developing pricing models for financial products to model risk, economics, and cash flows under normal and distressed market environments. ©The Goldman Sachs Group, Inc., 2026. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law. |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://hdpc.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_3002/job/175521 |
| Apply URL | https://hdpc.fa.us2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_3002/job/175521 |
| First Seen At | 2026-06-04 10:46:18Z |
| Last Seen At | 2026-06-06 20:40:56Z |
| Last Checked At | 2026-06-06 20:40:56Z |
| Last Changed At | 2026-06-04 10:46:18Z |
| Inactive At | — |
| Source Posted At | 2026-06-03 12:42:41Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=oracle_hcm/board=hdpc.fa.us2.oraclecloud.com|CX_3002/date=2026-06-06/2026-06-06T20-39-27-656Z-8407786fbf547d2f1974010775020dbac3462628e2475885323cfa7a0ce0bba3.json |
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