Offer summary

Qualifications:

8-12 years' experience in credit risk modelling across customer life cycle., Strong understanding of machine learning techniques and algorithms., Experience working with large data sets using Python and statistical modelling tools., Knowledge of decisioning and portfolio management in banking is a plus..

Key responsibilities:

Deliver high-quality analytical services for clients while adhering to timelines.

Build risk models leveraging bureau and alternate data.

Engage with business and technical teams to ensure a shared understanding of solutions.

Manage multiple complex analytics projects and mentor junior team members.

Job description

Company Description

Experian unlocks the power of data to create opportunities for consumers, businesses and society. We gather and analyse data in ways others can't. We help individuals take financial control and access financial services, businesses make smarter decision and succeed, lenders lend more responsibly, and organisations 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, experienced people and new ideas so we can help create a better tomorrow.

Job Description

Delivering high quality analytical and value-added services for clients while adhering to timelines
Build next in class risk Models for our Clients leveraging bureau and alternate data
Provide subject matter expertise on acquisition and limit assignment strategies
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
You will have the opportunity to use analysis and customer insights to develop value propositions for customers
Manage the delivery of multiple, complex analytics projects
Flexible and expertise to perform hands-on modelling work
Motivate project team to ensure quality deliverables and achieve milestones
Mentor and coach junior team members in model development process
Develop industry best practice on model development/validation
Drive high standards of customer service and proactive client communication throughout the project term

Qualifications

8-12 years' experience in credit risk modelling across customer life cycle
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, Decision Tree
Experience working on large data sets using Modern languages like Python
Good understanding and hands-on experience of statistical modelling/data analysis tools (SAS, Python) and techniques
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 advantage
Understanding of credit bureau would be an added advantage
Extensive experience of managing large projects
Experience of working in a financial services environment or Modelling department of International Banks
Able to interpret technical features into commercial benefits