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Analytics Integration Analyst

Pay
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Work setting
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Apply at Ford Motor Private

What you’ll work on

Full posting
  • Implement, test, validate, and maintain credit risk models and strategies, including scorecards, PD, LGD, EAD, and ECL models.

  • Develop code, perform data reconciliation and impact analysis, support production execution, and resolve implementation issues.

  • Collaborate with model development, IT, and business teams to deliver model enhancements and change requests.

From the employer’s posting
Key Responsibilities Implement, test, validate, and maintain credit risk models and strategies, including scorecards, PD, LGD, EAD, and ECL models. Develop code, perform data reconciliation and impact analysis, support production execution, and resolve implementation issues.
Implement, test, validate, and maintain credit risk models and strategies, including scorecards, PD, LGD, EAD, and ECL models. Develop code, perform data reconciliation and impact analysis, support production execution, and resolve implementation issues. Collaborate with model development, IT, and business teams to deliver model enhancements and change requests.
Develop code, perform data reconciliation and impact analysis, support production execution, and resolve implementation issues. Collaborate with model development, IT, and business teams to deliver model enhancements and change requests. Build reusable automation for batch testing, data comparison, validation, and reporting across legacy and modern platforms.

What you’ll bring

All qualifications

Core experience

  • 3+ years of experience in credit risk analytics, model implementation, or analytics solutions integration.
  • Familiarity with model risk management, governance, Linux, and relational databases.
  • Ownership of deliverables, attention to detail, and commitment to quality.
  • Ability to work independently and collaborate with global, cross-functional teams.

Preferred experience

  • Bachelor’s degree in computer science, data science, information systems, engineering, or a related field; master’s degree preferred.
Qualification wording
3+ years of experience in credit risk analytics, model implementation, or analytics solutions integration.
Familiarity with model risk management, governance, Linux, and relational databases.
Ownership of deliverables, attention to detail, and commitment to quality.
Ability to work independently and collaborate with global, cross-functional teams.
Bachelor’s degree in computer science, data science, information systems, engineering, or a related field; master’s degree preferred.
Education & alternatives
Education and Experience - Bachelor’s degree in computer science, data science, information systems, engineering, or a related field; master’s degree preferred. - 3+ years of experience in credit risk analytics, model implementation, or analytics solutions integration.

Tools in this posting

  • Python
  • R
  • SAS
Source — Tool mentions in context
Technical Skills - Strong programming skills in SAS / python / R or any programming knowledge - Basic understanding of credit risk concepts and IFRS 9/CECL, including PD, LGD, EAD, and ECL.
- Familiarity with model risk management, governance, Linux, and relational databases. - Exposure to GCP, mainframe systems, SAS Real-Time Decision Manager, and AI/agentic tools is an advantage. Soft Skills and Personal Attributes

Posting record

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Status in our records
Live
First seen by us
Nov 4, 2026today
Recorded sightings
1

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Job description

View original posting ↗


 

Job Description

We are seeking an analyst to implement and productionize credit risk models and analytics solutions across global platforms. The role bridges model development, IT, and business teams, with a focus on implementation accuracy, production support, process modernization, and automation.

 

 

 

Key Responsibilities

  • Implement, test, validate, and maintain credit risk models and strategies, including scorecards, PD, LGD, EAD, and ECL models.
  • Develop code, perform data reconciliation and impact analysis, support production execution, and resolve implementation issues.
  • Collaborate with model development, IT, and business teams to deliver model enhancements and change requests.
  • Build reusable automation for batch testing, data comparison, validation, and reporting across legacy and modern platforms.
  • Support cloud-based analytics workflows and explore opportunities for GenAI and agentic automation.
  • Maintain technical and process documentation, support audits and model governance, and drive continuous improvement.

Position Qualifications

Education and Experience

  • Bachelor’s degree in computer science, data science, information systems, engineering, or a related field; master’s degree preferred.
  • 3+ years of experience in credit risk analytics, model implementation, or analytics solutions integration.

Technical Skills

  • Strong programming skills in SAS / python / R or any programming knowledge 
  • Basic understanding of credit risk concepts and IFRS 9/CECL, including PD, LGD, EAD, and ECL.
  • Exposure to data validation, testing, reconciliation, impact analysis, and productionizing analytical models.
  • Familiarity with model risk management, governance, Linux, and relational databases.
  • Exposure to GCP, mainframe systems, SAS Real-Time Decision Manager, and AI/agentic tools is an advantage.

Soft Skills and Personal Attributes

  • Strong analytical, problem-solving, and communication skills.
  • Ownership of deliverables, attention to detail, and commitment to quality.
  • Ability to work independently and collaborate with global, cross-functional teams.
  • Adaptability, curiosity, and a continuous-improvement mindset.

 

Source details

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Location & working pattern

Chennai, Tamil Nadu

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