Data Scientist - Intermediate

Equifax; Pune District, Pimpri-Chinchwad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Equifax is seeking a Data Scientist to manipulate large data sets, integrate diverse data sources, and develop analytical approaches to meet business requirements. The role includes translating requests into use cases, preparing training data, and iterative algorithm development.

You will validate models across credit risk, marketing, and fraud, using Python and ML libraries, while collaborating with teams across geographies to ensure compliant, robust solutions.

Qualifications

• 2–5 years of experience in developing and/or validating models in financial domains.
• Master’s degree or higher in Statistics, Mathematics, Engineering, Economics, Data Science, or related field.

Responsibilities

• Independently validate models across financial domains (credit risk, marketing, fraud, account management).
• Utilize Google Cloud Platform (GCP) to automate workflows and improve integration.
• Execute AI validation projects from concept to implementation aligned with goals.
• Collaborate with departments to ensure cohesive strategy and share insights.
• Contribute to policies guiding AI practices and model risk management for regulatory compliance.
• Stay current with industry best practices and regulatory guidelines related to model risk management.

Skills

Python

SQL

Statistical modeling

Communication

Collaboration

Education

Master's degree or higher in Statistics/Mathematics/Engineering/Economics/Data Science

Tools

Scikit-learn

Statsmodels

TensorFlow

GCP

Job description

As a Data Scientist , you will have the opportunity to manipulate large data sets, integrate diverse data sources, data types and data structures into solutions under management guidance. You will build experience developing analytical approaches to meet business requirements, which involves translating requests into use cases, test cases, preparation of training data sets and iterative algorithm development.

What You Will Do

• Independently validate models across multiple financial domains, including consumer and commercial credit risk, marketing, fraud, account management to ensure their 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

What Experience You 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, demonstrating a high level of expertise and commitment to the field
• Demonstrated expertise in AI techniques (Machine learning, natural language processing, deep learning) and their applications.
• Experience with ML libraries such as Scikit-learn, Statsmodels, TensorFlow, or equivalent is recommended.
• Advanced level programming in Python and SQL.
• Strong interpersonal skills with the ability to build effective relationships and collaborate effectively 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.

What Could Set You Apart

• 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.