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Lead - Data Science

A7405949

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you.

Synopsis of the role

Join our Model Risk Management group as a Lead- Data Science, where you'll play a pivotal role in ensuring the accuracy and reliability of our models. Supervise projects and team members while delving into complex data sets across multiple domains. Collaborate with cross-functional teams to assess, validate, and enhance AI and ML models that serve the needs of our clients and help consumers live their financial best.

What you’ll do

Supervise and work as an independent contributor on model validations across multiple financial domains, including consumer and commercial credit risk, marketing, fraud, and AML. Ensure the accuracy, reliability, and compliance of models by overseeing and conducting thorough validations.

Utilize Google Cloud Platform(GCP) to enhance efficiency by automating workflows and improving process integration.

Drive AI validation projects by conceptualizing, planning, and executing them to ensure their successful implementation and 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.

Mentor and develop team members, fostering a culture of collaboration and building a robust, knowledgeable team.

Contribute to the design and execution of model testing and monitoring processes.

What experience you need

6+ years of experience of developing and validating models, with a deep understanding of industry-specific requirements and challenges.

Demonstrated expertise in AI techniques(Machine learning, natural language processing, deep learning), including exposure to Generative AI technologies and their applications. Experience with ML libraries such as TensorFlow, Keras, PyTorch and Scikit- learn required

Minimum of 1 year of experience in supervising projects and team members, demonstrating ability to successfully manage multiple projects and stakeholders simultaneously

Advanced level programming in Python and SQL 

Strong interpersonal skills with the ability to lead teams, manage client 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 and fraud models.

Ability to articulate complex concepts clearly and effectively to diverse stakeholders, ensuring understanding across various levels of technical proficiency.

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.

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 & AWS

Experience in prompt engineering for fining tuning Large language models such as GPT/Gemini or similar

We offer a hybrid work setting, comprehensive compensation and healthcare packages, attractive paid time off, and organizational growth potential through our online learning platform with guided career tracks.

Are you ready to power your possible? Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference!

El trabajo en Equifax

Creemos en una mentalidad de crecimiento. En Equifax, esto incluye brindar a nuestros empleados oportunidades para desempeñarse al máximo y aprender nuevas habilidades a lo largo del camino para inspirar y desarrollar carreras profesionales satisfactorias

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