Data Scientist - Intermediate

Equifax Inc.; Pune District; Presencial; INR 1.400.000 - 2.600.000; Jornada completa

Descripción de la vacante

Equifax Inc. is seeking a Data Scientist to develop and validate models across consumer and commercial credit risk, marketing, and fraud domains. You will translate requests into use cases, prepare training datasets, and iteratively develop analytical approaches under guidance.

You will validate models, leverage GCP for automation, and contribute to policy and risk management in a collaborative, regulatory-aware environment.

Formación

• 2-5 years of experience developing/validating models with industry-specific requirements.
• Master’s or higher in Statistics, Mathematics, Engineering, Economics, Data Science, or related field.
• Expertise in AI techniques (ML, NLP, DL) and their applications.
• Experience with ML libraries such as Scikit-learn, Statsmodels, TensorFlow, or equivalent.
• Advanced programming in Python and SQL.
• Strong interpersonal skills to build relationships and collaborate with partners.
• Experience collaborating with partners across geographies and levels.
• In-depth knowledge of credit risk, marketing and/or fraud models.

Responsabilidades

• Validate models across financial domains to ensure accuracy and compliance.
• Leverage GCP to automate workflows and improve integration.
• Lead AI validation projects from planning to implementation.
• Collaborate with departments to implement cohesive AI strategies.
• Contribute to policies guiding AI practices and model risk management.
• Keep abreast of industry best practices and regulatory guidelines.

Conocimientos

Python

SQL

AI techniques

Cross-functional collaboration

Interpersonal skills

Educación

Master’s degree or higher in Statistics/Math/Engineering/Economics/Data Science

Herramientas

Scikit-learn

Statsmodels

TensorFlow

Descripción del empleo

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.