Data Modeler I

Company Description

Experian unlocks the power of data to create opportunities for consumers, businesses and society. We gather, analyze and process data in ways others can’t. We help individuals take financial control and access financial services, businesses make smarter decision and thrive, lenders lend more responsibly, and organizations prevent identity fraud and crime. For more than 125 years, we’ve helped consumers and clients prosper, and economies and communities flourish – and we’re not done. Our 17,800 people in 45 countries believe the possibilities for you, and our world, are growing. We’re investing in new technologies, talented people and innovation so we can help create a better tomorrow.

Job Description

What you’ll need to bring to the party

• You’ll need to be a curious problem solver who can get a question and use data to answer in a clear and straightforward way
• You must be self-directed and comfortable supporting the data needs of multiple teams, systems and products
• We want you to be excited by the prospect of working with large and diverse datasets using cutting-edge techniques
• such as AI, machine learning and deep learning.
• Drive high standards of customer service and proactive client communication throughout the project term
• Develop industry best practice on model development/validation
• This role is responsible for efficiently and effectively managing multiple and complex projects from concept to implementation on time, within budget and in line with client expectations.
• You’ll play an integral role to Engage Business/Technical Consultants and delivery teams appropriately so that there is a shared understanding and agreement as to deliver proposed solution

Qualifications

Qualifications

• A strong understanding of machine learning techniques and algorithms, such as Gradient Boost, KNN, etc.
• Knowledge of different modelling frameworks like Linear Regression, Logistic Regression, Multiple
• egression, LOGIT, PROBIT, time- series modelling, CHAID, CART etc.
• Thorough understanding of the Application/Behaviour/Collection scorecard development process.
• Thorough knowledge of the use and application of analytical methodologies Linier Regression, Logistic
• Regression etc
• Decent understanding and hands-on of statistical modelling/data analysis tools (SAS, Python, R etc.), techniques and
• Good applied statistics skills, such as distributions, statistical testing, regression etc.
• Understanding of decisioning and portfolio management in banking and financial services would be added

Additional Information

Experian Careers - Creating a better tomorrow together

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