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Data Scientist

Efds Fa Em5 Oraclecloud Com CX 1 · GTBC Office Building 01, Chennai, TN, IN · Hybrid · Active · Oracle Recruiting Cloud / Fusion HCM

Job facts

FieldValue
CompanyEfds Fa Em5 Oraclecloud Com CX 1
TitleData Scientist
Normalized title-
Department / teamGlobal Data Insight & Analytics
LocationChennai, TN, United States
Work modelHybrid / Hybrid
Employment typeFull Time
Salary-
Statusactive
ATS providerOracle Recruiting Cloud / Fusion HCM
Posted / first seen2026-06-23 / 2026-06-06
Changed / last seen2026-06-23 / 2026-06-23

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PageWhat it containsOpen
Company jobsActive postings from Efds Fa Em5 Oraclecloud Com CX 1.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Oracle Recruiting Cloud / Fusion HCM.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Chennai.Open
Department jobsActive postings in Global Data Insight & Analytics.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyEfds Fa Em5 Oraclecloud Com CX 1
Sourced8110a61-5510-417b-a74c-f58816339c6b
ATS providerOracle Recruiting Cloud / Fusion HCM

Description

Description The Global Data Insights and Analytics (GDI&A) department at Ford Motor Company is looking for qualified people who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, Econometrics, and Optimization. The goal of GDI&A is to drive evidence-based decision making by providing insights from data. Applications for GDI&A include, but are not limited to, Connected Vehicle, Smart Mobility, Advanced Operations, Manufacturing, Supply chain, Logistics, and Warranty Analytics. Potential candidates should have hands-on experience in applying first principles methods, machine learning, data mining, and text mining techniques to build analytics prototypes that work on massive datasets. Candidates should have experience in manipulating both structured and unstructured data in various formats, sizes, and storage-mechanisms . Candidates should have excellent problem-solving skills with an inquisitive mind to challenge existing practices. Candidates should have exposure to multiple programming languages and analytical tools and be flexible to using the requisite tools/languages for the problem at-hand . Responsibilities Build data-driven models to understand the characteristics of engineering systems Apply machine learning, data mining and text mining techniques to create scalable solutions for business problems Train, tune, validate, and monitor predictive models Analyze and extract relevant information from large amounts of historical business data especially related to quality, product development, and connected vehicles, both in structured and unstructured formats Establish scalable, efficient, automated processes for large scale data analyses Package and present the findings and communicate with large cross-functional teams Qualifications BE, B.Tech , M.S. or Ph.D. in Data Science, Computer Science, Operations research , Statistics, Applied mathematics . 3+ years of hands-on experience in using machine learning/text mining tools and techniques such as Clustering/classification/decision trees, Random forests, Support vector machines, Deep Learning, Neural networks, Reinforcement learning, and other numerical algorithms 3+ years of experience in at least one of the following languages: Python, R, MATLAB, SAS Experience with GoogleCloud Platform (GCP) including VertexAI , BigQuery , DBT, NoSQL database Excellent problem solving, communication, and data presentation skills

Full job record

Job ID418f2831974a466b158bcc430f597611d024c9e7
Org IDfc791186-3bfa-4e9d-8648-0d2f6f66937d
Source IDd8110a61-5510-417b-a74c-f58816339c6b
Board IDd8110a61-5510-417b-a74c-f58816339c6b
Provideroracle_hcm
Provider Job Key64933
TitleData Scientist
Normalized Title—
Statusactive
Activeyes
Location TextGTBC Office Building 01, Chennai, TN, IN
DepartmentGlobal Data Insight & Analytics
Team—
Employment Typefull_time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionTN
CityChennai
Salary RawDescription The Global Data Insights and Analytics (GDI&A) department at Ford Motor Company is looking for qualified people who can develop scalable solutions to complex real-world problems using Machine Learning, Big Data, Statistics, Econometrics, and Optimization. The goal of GDI&A is to drive evidence-based decision making by providing insights from data. Applications for GDI&A include, but are not limited to, Connected Vehicle, Smart Mobility, Advanced Operations, Manufacturing, Supply chain, Logistics, and Warranty Analytics. Potential candidates should have hands-on experience in applying first principles methods, machine learning, data mining, and text mining techniques to build analytics prototypes that work on massive datasets. Candidates should have experience in manipulating both structured and unstructured data in various formats, sizes, and storage-mechanisms . Candidates should have excellent problem-solving skills with an inquisitive mind to challenge existing practices. Candidates should have exposure to multiple programming languages and analytical tools and be flexible to using the requisite tools/languages for the problem at-hand . Responsibilities Build data-driven models to understand the characteristics of engineering systems Apply machine learning, data mining and text mining techniques to create scalable solutions for business problems Train, tune, validate, and monitor predictive models Analyze and extract relevant information from large amounts of historical business data especially related to quality, product development, and connected vehicles, both in structured and unstructured formats Establish scalable, efficient, automated processes for large scale data analyses Package and present the findings and communicate with large cross-functional teams Qualifications BE, B.Tech , M.S. or Ph.D. in Data Science, Computer Science, Operations research , Statistics, Applied mathematics . 3+ years of hands-on experience in using machine learning/text mining tools and techniques such as Clustering/classification/decision trees, Random forests, Support vector machines, Deep Learning, Neural networks, Reinforcement learning, and other numerical algorithms 3+ years of experience in at least one of the following languages: Python, R, MATLAB, SAS Experience with GoogleCloud Platform (GCP) including VertexAI , BigQuery , DBT, NoSQL database Excellent problem solving, communication, and data presentation skills
Salary Min—
Salary Max—
Salary Currency—
Salary Period—
Source URLhttps://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/64933
Apply URLhttps://efds.fa.em5.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1/job/64933
First Seen At2026-06-06 11:48:38Z
Last Seen At2026-06-23 11:40:16Z
Last Checked At2026-06-23 11:40:16Z
Last Changed At2026-06-23 11:40:16Z
Inactive At—
Source Posted At2026-06-23 06:54:04Z
Source Updated At—
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=oracle_hcm/board=efds.fa.em5.oraclecloud.com|CX_1/date=2026-06-23/2026-06-23T11-38-45-351Z-13f91ac46509d8d1f971d9289e99ed078ee7738f9b19f6146f685ca405acd819.json
Event Fields
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font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; position: relative; text-align: start; text-decoration-line: none; text-decoration-style: solid; text-decoration-thickness: auto; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><ul><li><p class=\"Paragraph SCXW122301153 BCX4\" paraid=\"1748829155\" paraeid=\"{7a611e6e-3ae0-44b4-bab4-a34ff9df2cbd}{249}\" style=\"-webkit-user-drag: none; background-color: rgb(255, 255, 255); color: windowtext; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; 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background-repeat: repeat-x; border-bottom: 1px solid transparent; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">VertexAI</span><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">, </span><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun SpellingErrorV2Themed\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; background-position: 0px 100%; background-repeat: repeat-x; border-bottom: 1px solid transparent; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">BigQuery</span><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">, DBT, NoSQL database</span></span><span style=\"background-color: var(--clrSelection,#c6c6c6) !important; font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"EOP Selected SCXW122301153 BCX4\" data-ccp-props=\"{&quot;335557856&quot;:16777215}\" style=\"-webkit-user-drag: none; border-color: var(--clrSelection,#c6c6c6) !important; cursor: default; font-size: 11pt; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW122301153 BCX4\" style=\"-webkit-text-stroke-width: 0px; -webkit-user-drag: none; caret-color: rgba(0, 0, 0, 0.847); color: rgba(0, 0, 0, 0.847); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; 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-webkit-user-drag: none; caret-color: rgba(0, 0, 0, 0.847); color: rgba(0, 0, 0, 0.847); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; position: relative; text-align: start; text-decoration-line: none; text-decoration-style: solid; text-decoration-thickness: auto; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><ul><li><p class=\"Paragraph SCXW122301153 BCX4\" paraid=\"1566820768\" paraeid=\"{7a611e6e-3ae0-44b4-bab4-a34ff9df2cbd}{231}\" style=\"-webkit-user-drag: none; background-color: rgb(255, 255, 255); color: windowtext; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">3+ years of hands-on experience in using machine learning/text mining tools and techniques such as Clustering/classification/decision trees, Random forests, Support vector machines, Deep Learning, Neural networks, Reinforcement learning, and other numerical algorithms</span></span><span style=\"background-color: var(--clrSelection,#c6c6c6) !important; font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"EOP Selected SCXW122301153 BCX4\" data-ccp-props=\"{&quot;335557856&quot;:16777215}\" style=\"-webkit-user-drag: none; border-color: var(--clrSelection,#c6c6c6) !important; cursor: default; font-size: 11pt; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW122301153 BCX4\" style=\"-webkit-text-stroke-width: 0px; -webkit-user-drag: none; caret-color: rgba(0, 0, 0, 0.847); color: rgba(0, 0, 0, 0.847); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; position: relative; text-align: start; text-decoration-line: none; text-decoration-style: solid; text-decoration-thickness: auto; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><ul><li><p class=\"Paragraph SCXW122301153 BCX4\" paraid=\"1480257796\" paraeid=\"{7a611e6e-3ae0-44b4-bab4-a34ff9df2cbd}{237}\" style=\"-webkit-user-drag: none; background-color: transparent; color: windowtext; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">3+ years of experience in at least one of the following languages: Python, R, MATLAB, SAS</span></span><span style=\"background-color: var(--clrSelection,#c6c6c6) !important; font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"EOP Selected SCXW122301153 BCX4\" data-ccp-props=\"{}\" style=\"-webkit-user-drag: none; border-color: var(--clrSelection,#c6c6c6) !important; cursor: default; font-size: 11pt; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW122301153 BCX4\" style=\"-webkit-text-stroke-width: 0px; -webkit-user-drag: none; caret-color: rgba(0, 0, 0, 0.847); color: rgba(0, 0, 0, 0.847); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; position: relative; text-align: start; text-decoration-line: none; text-decoration-style: solid; text-decoration-thickness: auto; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><ul><li><p class=\"Paragraph SCXW122301153 BCX4\" paraid=\"1748829155\" paraeid=\"{7a611e6e-3ae0-44b4-bab4-a34ff9df2cbd}{249}\" style=\"-webkit-user-drag: none; background-color: rgb(255, 255, 255); color: windowtext; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">Experience with </span><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun SpellingErrorV2Themed\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; background-position: 0px 100%; background-repeat: repeat-x; border-bottom: 1px solid transparent; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">GoogleCloud</span><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\"> Platform (GCP) including </span><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun SpellingErrorV2Themed\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; background-position: 0px 100%; background-repeat: repeat-x; border-bottom: 1px solid transparent; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">VertexAI</span><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">, </span><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun SpellingErrorV2Themed\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; background-position: 0px 100%; background-repeat: repeat-x; border-bottom: 1px solid transparent; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">BigQuery</span><span class=\"TextRun SCXW122301153 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; 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font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">Apply machine learning, data mining and text mining techniques to create scalable solutions for business problems</span></span><span style=\"background-color: var(--clrSelection,#c6c6c6) !important; font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"EOP Selected SCXW137417511 BCX4\" data-ccp-props=\"{}\" style=\"-webkit-user-drag: none; border-color: var(--clrSelection,#c6c6c6) !important; cursor: default; font-size: 11pt; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW137417511 BCX4\" style=\"-webkit-text-stroke-width: 0px; -webkit-user-drag: none; caret-color: rgba(0, 0, 0, 0.847); color: rgba(0, 0, 0, 0.847); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; position: relative; text-align: start; text-decoration-line: none; text-decoration-style: solid; text-decoration-thickness: auto; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><ul><li><p class=\"Paragraph SCXW137417511 BCX4\" paraid=\"1797845851\" paraeid=\"{7a611e6e-3ae0-44b4-bab4-a34ff9df2cbd}{158}\" style=\"-webkit-user-drag: none; background-color: transparent; color: windowtext; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"TextRun SCXW137417511 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">Train, tune, validate, and monitor predictive models&nbsp;</span></span><span style=\"background-color: var(--clrSelection,#c6c6c6) !important; font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"EOP Selected SCXW137417511 BCX4\" data-ccp-props=\"{}\" style=\"-webkit-user-drag: none; border-color: var(--clrSelection,#c6c6c6) !important; cursor: default; font-size: 11pt; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW137417511 BCX4\" style=\"-webkit-text-stroke-width: 0px; -webkit-user-drag: none; caret-color: rgba(0, 0, 0, 0.847); color: rgba(0, 0, 0, 0.847); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; position: relative; text-align: start; text-decoration-line: none; text-decoration-style: solid; text-decoration-thickness: auto; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><ul><li><p class=\"Paragraph SCXW137417511 BCX4\" paraid=\"487377381\" paraeid=\"{7a611e6e-3ae0-44b4-bab4-a34ff9df2cbd}{164}\" style=\"-webkit-user-drag: none; background-color: transparent; color: windowtext; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"TextRun SCXW137417511 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">Analyze and extract relevant information from large amounts of historical business data especially related to quality, product development, and connected vehicles, both in structured and unstructured formats</span></span><span style=\"background-color: var(--clrSelection,#c6c6c6) !important; 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line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">Train, tune, validate, and monitor predictive models&nbsp;</span></span><span style=\"background-color: var(--clrSelection,#c6c6c6) !important; font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"EOP Selected SCXW137417511 BCX4\" data-ccp-props=\"{}\" style=\"-webkit-user-drag: none; border-color: var(--clrSelection,#c6c6c6) !important; cursor: default; font-size: 11pt; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">&nbsp;</span></span></p></li></ul></div><div class=\"ListContainerWrapper SCXW137417511 BCX4\" style=\"-webkit-text-stroke-width: 0px; -webkit-user-drag: none; caret-color: rgba(0, 0, 0, 0.847); color: rgba(0, 0, 0, 0.847); font-family: &quot;Segoe UI&quot;, &quot;Segoe UI Web&quot;, Arial, Verdana, sans-serif; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; margin: 0px; orphans: 2; padding: 0px; position: relative; text-align: start; text-decoration-line: none; text-decoration-style: solid; text-decoration-thickness: auto; text-indent: 0px; text-transform: none; user-select: text; white-space: normal; widows: 2; word-spacing: 0px;\"><ul><li><p class=\"Paragraph SCXW137417511 BCX4\" paraid=\"487377381\" paraeid=\"{7a611e6e-3ae0-44b4-bab4-a34ff9df2cbd}{164}\" style=\"-webkit-user-drag: none; background-color: transparent; color: windowtext; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"TextRun SCXW137417511 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">Analyze and extract relevant information from large amounts of historical business data especially related to quality, product development, and connected vehicles, both in structured and unstructured formats</span></span><span style=\"background-color: var(--clrSelection,#c6c6c6) !important; 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widows: 2; word-spacing: 0px;\"><ul><li><p class=\"Paragraph SCXW137417511 BCX4\" paraid=\"246027765\" paraeid=\"{7a611e6e-3ae0-44b4-bab4-a34ff9df2cbd}{172}\" style=\"-webkit-user-drag: none; background-color: transparent; color: windowtext; font-style: normal; font-weight: normal; margin: 0px; overflow-wrap: break-word; padding: 0px; text-align: left; text-indent: 0px; user-select: text; vertical-align: baseline;\"><span style=\"font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"TextRun SCXW137417511 BCX4 NormalTextRun\" data-contrast=\"auto\" xml:lang=\"EN-US\" lang=\"EN-US\" style=\"-webkit-user-drag: none; font-size: 11pt; font-variant-ligatures: none !important; line-height: 17px; margin: 0px; padding: 0px; user-select: text;\">Establish scalable, efficient, automated processes for large scale data analyses</span></span><span style=\"background-color: var(--clrSelection,#c6c6c6) !important; font-family: Calibri, Calibri_EmbeddedFont, Calibri_MSFontService, sans-serif;\"><span class=\"EOP Selected SCXW137417511 BCX4\" data-ccp-props=\"{}\" style=\"-webkit-user-drag: none; 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        "PostalCode": "600119",
        "TownOrCity": "Chennai",
        "AddressLine1": "15 Plot No 13",
        "AddressLine2": "Survey No 602, 3 And 16, Sholinganallur, Elcot Sez",
        "AddressLine3": null,
        "AddressLine4": null,
        "LocationName": "GTBC Office Building 01"
      }
    ],
    "LegalEmployer": null,
    "MediaThumbURL": null,
    "WorkplaceType": "Hybrid",
    "BusinessUnitId": 300000004330057,
    "OrganizationId": 300000004330057,
    "PostingEndDate": null,
    "LegalEmployerId": 300000004978854,
    "PrimaryLocation": "Chennai, Tamil Nadu, India",
    "WorkDurationYears": null,
    "WorkplaceTypeCode": "ORA_HYBRID",
    "BeFirstToApplyFlag": false,
    "WorkDurationMonths": null,
    "otherWorkLocations": [],
    "secondaryLocations": [],
    "ShortDescriptionStr": "Strong Data Scientist with the love for solving problems to join a highly functional team of data scientists and software engineers.",
    "requisitionFlexFields": [],
    "DomesticTravelRequired": null,
    "PrimaryLocationCountry": "IN",
    "ExternalQualificationsStr": null,
    "ExternalResponsibilitiesStr": null,
    "InternationalTravelRequired": null
  },
  "detail_meta": {
    "url": "https://efds.fa.em5.oraclecloud.com/hcmRestApi/resources/latest/recruitingCEJobRequisitionDetails?expand=all&onlyData=true&finder=ById;Id=%2264933%22,siteNumber=CX_1",
    "http_status": 200,
    "content_type": "application/json",
    "response_bytes": 59561
  },
  "detail_errors": []
}
Get this page with API

Rendered from the bluedoor Job Postings API. Reproduce it:

GET https://api.bluedoor.sh/job-postings/v1/jobs/418f2831974a466b158bcc430f597611d024c9e7?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/fc791186-3bfa-4e9d-8648-0d2f6f66937dJSON
GET https://api.bluedoor.sh/job-postings/v1/sources/d8110a61-5510-417b-a74c-f58816339c6bJSON
GET https://api.bluedoor.sh/job-postings/v1/jobs/418f2831974a466b158bcc430f597611d024c9e7/eventsJSON

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