Data Scientist - Intermediate

Overview

Equifax is hiring a Data Scientist to manipulate large data sets, integrate diverse data sources, and develop analytical approaches to meet business requirements under management guidance.

What you'll do

• Independently validate models across financial domains, including consumer and commercial credit risk, marketing, fraud, and account management, to ensure accuracy, reliability, and compliance.
• Utilize Google Cloud Platform (GCP) to enhance efficiency by automating workflows and improving process integration.
• Execute AI validation projects, contributing to their conceptualization, planning, and successful implementation in alignment with organizational goals.
• Engage with various departments to ensure cohesive strategy implementation, sharing insights, and fostering a collaborative work environment.
• Contribute expertise to the development of policies that guide AI practices and model risk management, ensuring regulatory compliance and ethical standards.
• Stay current with industry best practices and regulatory guidelines related to model risk management.
• Translate requests into use cases, test cases, preparation of training data sets, and iterative algorithm development.

What you'll need

• 2 - 5 years of experience in developing and/or validating models, with a good understanding of industry-specific requirements and challenges.
• Master's degree or higher in Statistics, Mathematics, Engineering, Economics, Data Science, or other relevant discipline.
• Demonstrated expertise in AI techniques (machine learning, natural language processing, deep learning) and their applications.
• Advanced level programming in Python and SQL.
• Strong interpersonal skills with the ability to build effective relationships and collaborate with partners.
• Experience collaborating with partners, stakeholders, and teams across multiple geographies and levels of the organization.
• In-depth knowledge and practical experience in credit risk, marketing and/or fraud models.

Nice to have

• Experience with ML libraries such as Scikit-learn, Statsmodels, TensorFlow, or equivalent.
• Exposure to AI agents, multi-agents and/or Agentic AI frameworks.
• 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 and/or AWS.
• Excellent communication and presentation skills.

Details

• Location: Pune, India.
• Work setting: Hybrid.
• Schedule: Full time.