Data Scientist

Design, build, and optimize predictive models and machine learning pipelines to support business strategy and customer decision points.

Extract, clean, and feature-engineer large-scale structured and unstructured datasets using statistical and computing tools.

Translate complex business requirements into automated, reusable analytical components and scalable data products.

Present technical findings, model performance metrics, and business impact to mid-level leadership and external stakeholders.

Conduct code and model reviews for peer and junior data scientists to maintain high accuracy, reproducibility, and governance standards.

Bachelor's or Master's degree in a STEM field (Data Science, Statistics, Computer Science, or related quantitative discipline).

5–7 years of hands-on experience in predictive modeling, statistical analysis, and machine learning deployment in real-world applications.

Advanced proficiency in Python and SQL for data manipulation, analysis, and algorithm development.

Demonstrated experience in feature development, model performance evaluation, and hyperparameter optimization.

Practical hands-on experience working within enterprise cloud platforms (GCP, AWS, or Azure).

Prior domain experience in financial services, specifically credit risk, marketing analytics, or collections.

Experience handling large-scale datasets using PySpark, BigQuery, Snowflake, or Hadoop platforms.

Google Cloud Platform (GCP) certifications (e.g., Professional Data Engineer or Professional Machine Learning Engineer).

Proficiency with Git version control, CI/CD pipelines, and MLOps best practices.

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!