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Data Scientist at Equifax — Trivandrum

Experience5–7 yrs
SalaryNot disclosed
Work modeonsite
Levelsenior
Posted15 Sept 2026

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About Equifax

Equifax is hiring in Trivandrum in financial services. This role looks for around 5+ years of experience.

Skills

Predictive modeling
Machine learning
Python
SQL
Statistical analysis
Feature engineering
Model performance evaluation
Hyperparameter optimization
Cloud platforms

The role

A data scientist at a financial services company builds predictive models and machine learning pipelines for consumer lending decisions, using Python and SQL to turn complex data into scalable analytical products. The work also applies credit risk, statistical analysis, and cloud platforms to evaluate model performance and support data-driven business strategy.

Full job description

We are seeking an experienced and driven Data Science expert to join the Analytical Capabilities team, where you will help power Equifax’s AI and analytical offerings. In this role, you will build innovative tools and perform in-depth analysis to support customer decision points across the consumer lending lifecycle. By leveraging advanced mathematical and statistical approaches, you will develop robust, reusable, and highly automated solutions.

In this position, you will analyze complex data sources using various programming languages to inform business strategy and deliver insights for both internal and external stakeholders. You will develop models to test hypotheses and quantify the impact of decisions under various scenarios. Your ability to communicate technical results will be essential in driving profitability and translating business requirements into scalable, data-driven products.

What you'll do:

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.

What experience you need:

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).

What could set you apart:

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.