Job Description Job description Essential Duties and Responsibilities • Handle the delivery of multiple, complex analytics projects to clients from inception to completion • Open to hands-on modelling work • Manage (small) projects to achieve milestones /manage& motivate project team to ensure quality deliverables • Mentor and coach junior team members in model development process • Drive high standards of customer service and proactive client communication throughout the project term • Proactively communicate project status and deliverables through the life of the project • Ensure issues raised by the client are resolved in a timely and efficient manner • Prepare and deliver structured model development/validation training courses to the SEA clients • Flexible to travel to client locations on short notice for project delivery(30%) Knowledge & Experience • Up to 0-5 years' experience in credit risk modelling across customer life cycle • Expert in any two analytical programing languages SAS,Python and R • Comfortable with large data sets • 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 • Thorough understanding of segmentation techniques CHAID, CART etc.
• Good understanding of PD, EAD and LGD model development & validation process.
• Significant experience of statistical / analytics project work • Experience of working in a financial services environment or Modelling department of International Banks • Strong analytical skills.
• Excellent communication and interpersonal skills.
Qualifications • Degree or equivalent standard, with a high numeric content e.g.
Mathematics, Statistics, Operational Research, Economics, Physical Sciences.
• Graduate calibre, with formal project management skills/qualifications.
Qualifications Qualifications • Hands-on experience processing and analyzing data by using tools such as Python, R etc.• Good applied statistics skills, such as distributions, statistical testing, regression etc.• Good understanding of model predictive model development (such as Credit risk models, Fraud models etc.
).• 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, MultipleRegression, LOGIT, PROBIT, time- series modelling, CHAID, CART etc.• Understanding of decisioning and portfolio management in banking and financial services would be addedadvantage Additional Information Our uniqueness is that we truly celebrate yours.
Experian's culture and people are key differentiators.
We take our people agenda very seriously and focus on what truly matters; DEI, work/life balance, development, authenticity, engagement, collaboration, wellness, reward & recognition, volunteering... the list goes on.
Experian's strong people first approach is award winning; Great Place To Work in 24 countries, FORTUNE Best Companies to work and Glassdoor Best Places to Work (globally 4.4 Stars) to name a few.
Check out Experian Life on social or our Careers Site to understand why.
Experian is proud to be an Equal Opportunity and Affirmative Action employer.
Innovation is a critical part of Experian's DNA and practices, and our diverse workforce drives our success.
Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age.
If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
Experian Careers - Creating a better tomorrow together Find out what its like to work for Experian by clicking here