senior analyst

Ford Motor Company; Chennai District; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Ford Motor Company in Chennai seeks an experienced Credit Risk Analytics professional to implement, validate, and productionalize risk models across global platforms. You will collaborate with data scientists, IT and business teams to ensure smooth transition from development to production and apply IFRS9/CECL concepts where needed.

Your role requires 3+ years of hands-on experience, strong SAS/SQL skills, knowledge of risk modelling concepts, and a proactive approach to automation and process

Qualifications

• 3+ years of experience in Credit Risk Analytics or Model Implementation.
• Strong programming experience in Base SAS and SAS Enterprise Guide.
• Good understanding of credit risk modelling concepts, model implementation pipeline, risk scoring process, IFRS9/CECL concepts, including PD, LGD, EAD, and ECL.
• Experience with SQL, data validation, testing, impact analysis and production support.
• Knowledge of Model Risk Management / Model Governance frameworks and practices.
• Working knowledge of the Linux environment.
• Exposure to Python, Google Cloud Platform (GCP), or automation tools is an added advantage.
• Exposure to AI/LLM model usage is an added advantage.
• Exposure to Banking or Non-Banking Financial Lending is an added advantage.
• Implement, validate, test, and Productionalize predictive models and risk strategies across global platforms.
• Collaborate with Data Scientists, Business teams, and IT to ensure smooth transition of models from development to production.
• Implement and maintain credit risk models (Scorecard models, PD, LGD, other risk models) using SAS.
• Perform code development, testing, reconciliation, and production deployment for model enhancements and business logic changes.
• Support production execution and impact analysis and resolve implementation issues within agreed timelines.
• Collaborate with Model Development, IT, and business stakeholders to implement model enhancements and change requests.
• Prepare technical and workflow/process documentation and support internal and external audits.
• Drive automation and continuous process improvements by proactively identifying opportunities to enhance operational efficiency.
• Identify opportunities to introduce automation, GenAI tooling, and workflow simplification and develop Proof-of-Concepts, and enhance delivery processes through automation.
• Provide data analysis, SQL/SAS/Python programming, and on-demand reporting aligned to business needs.

Responsibilities

• 3+ years of experience in Credit Risk Analytics or Model Implementation.
• Strong programming experience in Base SAS and SAS Enterprise Guide.
• Implement and maintain credit risk models (PD, LGD, EAD) using SAS.
• Collaborate with Data Scientists, IT and business teams to productionize models.
• Drive automation and GenAI tooling to improve delivery processes.

Skills

Base SAS

SAS Enterprise Guide

SQL

Python

Linux

GCP

Automation

GenAI tooling

Credit risk modelling

IFRS9/CECL

Education

Bachelor's degree in Computer Science / Data Science / Information Systems / Engineering

Tools

SAS

SAS Enterprise Guide

SQL

Python

Linux

Google Cloud Platform

Job description

Job Description:

Note: When applying for this position, please ensure you use your external-facing profile / resume to avoid screening rejection.

• Looking for SG5/SG6 candidates.
• 3+ years of experience in Credit Risk Analytics or Model Implementation.
• Strong programming experience in Base SAS and SAS Enterprise Guide.
• Good understanding of credit risk modelling concepts, model implementation pipeline, risk scoring process, IFRS9/CECL concepts, including PD, LGD, EAD, and ECL.
• Experience with SQL, data validation, testing, impact analysis and production support.
• Knowledge of Model Risk Management / Model Governance frameworks and practices.
• Working knowledge of the Linux environment.
• Exposure to Python, Google Cloud Platform (GCP), or automation tools is an added advantage.
• Exposure to AI/LLM model usage is an added advantage.
• Exposure to Banking or Non-Banking Financial Lending is an added advantage.
• Implement, validate, test, and Productionalize predictive models and risk strategies across global platforms.
• Collaborate with Data Scientists, Business teams, and IT to ensure smooth transition of models from development to production.
• Implement and maintain credit risk models (Scorecard models, PD, LGD, other risk models) using SAS.
• Perform code development, testing, reconciliation, and production deployment for model enhancements and business logic changes.
• Support production execution and impact analysis and resolve implementation issues within agreed timelines.
• Collaborate with Model Development, IT, and business stakeholders to implement model enhancements and change requests.
• Prepare technical and workflow/process documentation and support internal and external audits.
• Drive automation and continuous process improvements by proactively identifying opportunities to enhance operational efficiency.
• Identify opportunities to introduce automation, GenAI tooling, and workflow simplification and develop Proof-of-Concepts, and enhance delivery processes through automation.
• Provide data analysis, SQL/SAS/Python programming, and on-demand reporting aligned to business needs.
• Bachelor’s degree in computer science, Data Science, Information Systems, Engineering, or related field required.
• Strong analytical, critical thinking, and problem-solving abilities.
• Strong ownership mindset with accountability for deliverables.
• Ability to learn new tools and technologies quickly.
• Excellent interpersonal and communication skills.
• Ability to work independently with minimal supervision.
• Proactive, curious, and willing to ask questions to uncover opportunities.
• Commitment to building efficient, scalable, and high-quality analytics solutions.
• Attention to detail with a commitment to delivering high-quality solutions.
• Flexible and adaptable, able to take on diverse responsibilities while consistently meeting delivery timelines to the highest quality standards.
• Ability to collaborate effectively in a global, cross-functional environment.

Requirements: