Data Scientist - Specialist

Equifax; Pune District, Pimpri-Chinchwad; On-site; INR 2,800,000 - 4,200,000; Full time

Job summary

Equifax in Pune is seeking a Data Scientist - Specialist to lead the Model Risk Management team, validating statistical and AI models while advising on risk governance and regulatory compliance.

You will oversee multiple validation projects, collaborate with global partners, and drive enhancements to model risk procedures in line with evolving regulations and industry best practices.

Qualifications

• Master’s degree in statistics, data science, CS, or related field.
• 7+ years in predictive modeling or data science, with credit risk preferred.
• Minimum 3 years managing a team of 6+ people.
• Strong knowledge of ML/forecasting techniques, including logistic and time series.
• Proficient in SAS, SQL, R, Python; cloud and UNIX/Linux experience.

Responsibilities

• Lead, manage, and mentor a team of model validators.
• Oversee multiple validation projects from design to delivery.
• Collaborate with global partners on AI/Model Risk governance.
• Perform independent model validations and deep-dive analyses.
• Develop validation test designs to assess model soundness.
• Review model documentation, code, and materials.

Skills

Model Validation

Statistical Modeling

Data Science

Generative AI

Agentic AI

Big Data

Python

Education

Master’s degree in statistics/data science/CS

Tools

SAS

SQL

R

Python

Scala

Spark

UNIX/Linux

Google Cloud

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.