Credit Data Scientist

Masters in Finance, Financial Engineering, Analytics or Mathematics, Computer Science, Statistics, Industrial Engineering, Operations research, or related field. 

Good understanding of Probability of Default (PD), LGD and EAD modeling technique.

Proven hand-on experience in Artificial Intelligence and extensive experience in GCP .

Very good understanding of Predictive modeling techniques and their application.

Knowledge of Credit life cycle

Statistics and machine learning techniques.

Conducted and applied statistical methodologies including linear regression, logistic regression, ANOVA/ANCOVA, CHAID/CART, cluster analysis

Team player and collaboration skills.

Programming skills in GCP, R, SAS, and PYTHON.

Fluency with Excel, PowerPoint and Word 

Strong written and oral presentation / communication skills – must have the ability to convey complex information simply and clearly

Experience with developing and implementing cloud based analytical solutions in GCP or similar set up.

Develop and validate credit risk models

Enhance the usage of Artificial Intelligence / ML and transform into more efficient solutions.

Using GCP, SAS, R, Python, for model building and model validation

Continual enhancement of statistical techniques and their applications in solving business objectives

Compile and analyze the results from modeling output and translate into actionable insights

Prepare PowerPoint presentations and document preparation for the entire credit risk modeling process

Collaborate, Support, Advise and Guide in development of the models

Acquire and share deep knowledge of data utilized by the team and its business partners

Participate in global conference calls and meetings as needed and manage multiple customer interfaces

Execute analytics special studies and ad hoc analyses

Evaluate new tools and technologies to improve analytical processes 

Set own priorities and timelines to accomplish projects (accountability for project deliverables)

Masters in Mathematics/Statistics/Economics/Engineering or any other related discipline or a track record of performance that demonstrate this ability

Practical applications of mathematical modeling and Artificial Intelligence

Demonstrated knowledge in credit and/or market risk measurement and management

Excellent problem solving, communication, and data presentation skills

Proficient with GCP, SAS, SQL, Python