MRM Consultant, Data Science & Analytics

TransUnion

Consultant in data science focusing on model governance and analytics for credit risk management. Collaborates on consumer credit models and ensures regulatory compliance for TransUnion's clients.

Posted 6/2/2026full-timePune • 🇮🇳 IndiaMid-LevelSeniorWebsite

ATS Keywords

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Hard Skills

model validationrisk managementquantitative analyticsperformance testingbenchmarkingback-testingdata ingestiondata quality controlPythonR

Soft Skills

communication skillsproject managementcollaborationanalytical thinkingproblem-solving

Tools & Technologies

SQLHadoopSparkbusiness intelligence solutions

Industry Keywords

model governanceregulatory complianceconceptual soundnessSR 11-7OCC 2011-12

Tech Stack

Tools & technologies

HadoopPythonSparkSQL

About the role

Key responsibilities & impact

Responsible for model governance of data-driven solutions related to IT infrastructure/operations, data ingestion and quality control, and enhancing customer experience.
Monitor & govern consumer credit models, strategies, and business intelligence solutions through consulting engagements and research.
Independently validate and review models across their lifecycle to ensure conceptual soundness, data integrity, and regulatory compliance.
Perform quantitative testing, benchmarking, and back-testing to assess model performance and stability using languages such as R, Python, SQL, Hive, and Spark.
Identify model limitations, assumptions, and potential risks, and recommend mitigation strategies.
Prepare comprehensive validation reports and effectively communicate findings to model owners, senior management, and regulatory stakeholders.
Contribute to strengthening the organization’s model risk governance framework by ensuring adherence to internal policies and industry standards.

Requirements

What you’ll need

Bachelor’s degree in statistics, mathematics, engineering, economics, or another highly quantitative field.
At least 5 years of professional experience in model validation, risk management, or quantitative analytics.
Excellent understanding of model development and validation techniques, including conceptual soundness, performance testing, benchmarking, and back-testing.
Familiarity with regulatory guidelines such as SR 11-7 and OCC 2011-12.
Proficiency in Python, R, SQL; experience with big data tools (Hadoop, Spark) is a plus.
Excellent communication skills for preparing validation reports and presenting findings to stakeholders.
Ability to work in a fast-paced, collaborative environment and manage multiple assignments effectively.
Strong project management skills with the ability to manage multiple assignments effectively.

Benefits

Comp & perks

Flexible time off
Workplace flexibility
Support for continued learning through tuition reimbursement, conferences, and seminars