Analytics Integration Analyst
Chennai, Tamil Nadu, India
Actively hiring, first seen by us today- Pay
- Pay not listed
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingImplement, test, and validate credit risk models, scorecards, and strategies
Perform data reconciliation and impact analysis, and resolve implementation issues
Build reusable automation for batch testing, data comparison, and validation
Deliver model enhancements and change requests with model, IT, and business teams
Maintain technical documentation and support audits and model governance
From the employer’s 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.
Build reusable automation for batch testing, data comparison, validation, and reporting across legacy and modern platforms.
Collaborate with model development, IT, and business teams to deliver model enhancements and change requests.
Maintain technical and process documentation, support audits and model governance, and drive continuous improvement.
What you’ll bring
All qualificationsCore 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
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 4, 2026today
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Chennai, Tamil Nadu, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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