Data Scientist - Specialist

Equifax Inc.; Pune District; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Equifax, Inc. is seeking a Data Scientist - Specialist to lead the Model Risk Management team in validating statistical and advanced AI models.

This senior role combines technical oversight, mentorship, and advisory duties to ensure risk governance and regulatory compliance. The position requires 7+ years of quantitative experience, leadership in model validation, and expertise in generative and agentic AI, big data, and cloud environments.

Qualifications

• Master's degree in a quantitative field such as statistics, data science, computer science, mathematics, economics, or finance.
• 7+ years of industry experience in predictive modeling, data science, or a related quantitative field. Prior experience with credit risk model development and/or validation is highly preferred.
• Minimum of 3 years managing a team with 6+ direct reports is preferred.
• Strong knowledge of advanced forecasting analytics or ML techniques including generative and agentic AI.
• Experience with Big Data environments and advanced computational processes.
• Demonstrated experience with model risk management and/or compliance is highly preferred.
• Excellent written and verbal communication skills; ability to write high-quality technical reports.
• Proficiency with SAS, SQL, R, Python, Scala, Spark; UNIX/LINUX; and cloud environments (GCP/AWS/Azure).
• Detail-oriented, proactive, and efficient.

Responsibilities

• Lead, manage, and mentor a high-performing team of model validators and oversee multiple validation projects from design to delivery.
• Foster critical thinking, continuous improvement, and risk management within the team.
• Collaborate with global partners to ensure consistent validation practices across regions.
• Perform hands-on model validations including deep-dive analysis of design, performance, and implementation.
• Develop and execute validation test designs to assess model soundness and risks.
• Assess model documentation, code, and marketing materials for completeness and accuracy.
• Research emerging analytical techniques, focusing on generative and agentic AI in validations.
• Develop innovative validation approaches for complex models with unstructured data.
• Advise model developers and business owners on risk mitigation and design considerations.
• Review model monitoring plans and performance reports; contribute to governance framework.

Skills

Leadership

Data science

Model risk

Analytical thinking

Communication skills

Regulatory knowledge

Education

Master's degree in quantitative field

Tools

SAS

SQL

R

Python

Scala

Spark

UNIX/LINUX

Google Cloud (GCP)

Job description

The Data Scientist - Specialist at Equifax leads the Model Risk Management team in validating statistical and advanced AI models. This strategic role combines hands-on technical oversight, team mentorship, and advisory duties regarding risk governance and regulatory compliance. Candidates require 7+ years of quantitative experience, proven leadership skills, and expertise in emerging technologies like generative and agentic AI.

What you'll do

• Lead, manage, and mentor a high-performing team of model validators, ensuring their professional growth and development.

• Oversee the execution of multiple complex validation projects simultaneously, from test design to final delivery and communication.

• Foster a culture of critical thinking, continuous improvement, and effective risk management within the team.

• Collaborate with global partners to supervise validation projects, ensuring a consistent and technically sound approach to AI/Model Risk Management across non-direct reporting lines

• Perform and lead independent, hands-on model validations, including deep-dive analysis of model design, performance, and implementation.

• Develop and execute comprehensive validation test designs to assess model soundness and identify potential risks.

• Critically assess the completeness and accuracy of model documentation, code, and marketing materials.

• Conduct deep-dive research on emerging analytical techniques, with a particular focus on validating models using generative AI and agentic AI.

• Develop and implement innovative validation approaches for complex and nontraditional models, including those with unstructured data and unique risk profiles.

• Serve as a trusted advisor to model developers and business owners on model design, development, and risk mitigation strategies.

• Review and provide guidance on model monitoring plans and ongoing performance reports.

• Drive the enhancement of Model Risk Management procedures and standards to align with evolving regulatory requirements and industry best practices.

• Collaborate with key stakeholders across the organization, including marketing, technology, legal, compliance, and business owners, to ensure a robust model risk governance framework.

• Respond to and manage inquiries from clients, internal auditors, and regulators regarding model risk matters.

What experience you need

• Master's degree in a quantitative field such as statistics, data science, computer science, mathematics, economics, or finance.

• 7+ years of industry experience in predictive modeling, data science, or a related quantitative field. Prior experience with credit risk model development and/or validation is highly preferred.

• A minimum of 3 years of experience managing a highly talented team with 6 or more direct reports is preferred.

• Strong knowledge of and hands-on experience with either advanced forecasting analytics (e.g., logistic regression, time series modeling, ML classification models)) or advanced machine learning techniques including generative AI and agentic AI.

• Extensive experience with Big Data environments and advanced computational processes.

• Demonstrated experience with model risk management and/or compliance is highly preferred.

• Exceptional critical thinking, problem-solving, and analytical skills.

• Proven ability to quickly grasp complex concepts and identify potential model issues or validation gaps.

• Excellent interpersonal, networking, verbal, and written communication skills, with a proven ability to write and edit high-quality technical reports.

• Proficiency with programming languages such as SAS, SQL, R, Python, Scala, and Spark.

• Hands-on experience with UNIX/LINUX and Google cloud environments.

• Highly detail-oriented, proactive, and efficient.

What could set you apart

• Familiarity with regulatory requirements and guidelines related to Model Risk Management.

• Prior regulatory modeling development experience including ECL, Stress testing, CECL/IFRS9.

• First-hand experience on cloud-based platforms including GCP, Azure, or AWS.

• Exposure to AI agents, multi-agents and/or Agentic AI Frameworks.

• Excellent communication and presentation skills.