
10,000+ employees
Founded 1996
💼 Consulting
📣 Marketing
📦 Logistics
Consulting • Marketing • Logistics
Experian is a global leader in digital experience, technology, and transformation. They partner with recognized brands to enhance customer understanding, innovate product strategies, and implement agile technology solutions. With a focus on delivering superior customer experiences through AI, cloud architecture, and project management, Experian helps businesses streamline their operations and achieve their objectives effectively.
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10,000+ employees
Founded 1996
💼 Consulting
📣 Marketing
📦 Logistics
Consulting • Marketing • Logistics
Experian is a global leader in digital experience, technology, and transformation. They partner with recognized brands to enhance customer understanding, innovate product strategies, and implement agile technology solutions. With a focus on delivering superior customer experiences through AI, cloud architecture, and project management, Experian helps businesses streamline their operations and achieve their objectives effectively.
• Develop statistical and Machine Learning models for credit, risk, and other analytical applications • Lead the full model development lifecycle, from data exploration and preparation through validation, documentation, and deployment • Work with large structured and unstructured datasets, identifying opportunities to generate value • Evaluate model performance using statistical and business metrics, proposing continuous improvements • Collaborate with Product, Engineering, Analytics, Sales, and Client teams to transform business needs into analytical solutions • Monitor model performance in production and propose monitoring, recalibration, and evolution strategies • Contribute to the dissemination of best practices in modeling, programming, and analytics governance • Serve as a technical reference for junior analysts, supporting their development
• Bachelor’s degree in Statistics, Mathematics, Engineering, Computer Science, Economics, Physics, or a related field • Strong experience developing statistical and/or Machine Learning models • Knowledge of credit modeling (Application, Behaviour, Collections, or regulatory models) is a significant advantage • Proficiency in Python and/or SAS • Experience with SQL and handling large datasets • Knowledge of supervised and unsupervised Machine Learning techniques • Knowledge of applied statistics, model validation, and metrics such as KS, Gini, AUC, and PSI, among others • Experience using Git or version control tools • Strong communication skills, with the ability to present technical results to diverse audiences • Experience with PySpark, Databricks, or distributed environments • Knowledge of MLOps and deploying models into production • Experience with alternative-data-based models • Knowledge of regulations related to credit risk management • Analytical, problem-solving mindset • Intellectual curiosity and an interest in innovation • Ability to transform data into business insights • Collaborative team player • Proactive mindset and strong sense of ownership • Comfortable working in dynamic environments with multiple projects
• Remote work • Inclusive, purpose-driven environment • Career opportunities and professional experiences • An environment that supports balancing career with personal commitments and interests • Focus on well-being • Great Place To Work™ recognition • Top Employers certification • 4.6 rating on Glassdoor
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