Job Description :

- 7+ years exp on Python, ML and model development.

- Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development : Design, build, and implement credit risk model.

- Contribute to how analytical approach is structured for specification of analysis.

- Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems.

- 8+ years exp on ML/Python (predictive modelling).

- Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business.

- Create experiments and prototype implementations of new learning algorithms and prediction techniques.

- Collaborate with product managers, and stockholders to design and implement software solutions for science problems.

- Use machine learning best practices to ensure a high standard of quality for all of the team deliverables.

- Has experience working on unstructured data ( text ) : Text cleaning, TFIDF, text vectorization.

- Hands-on experience with IFRS 9 models and regulations.

- Data Analysis : Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity.

- Statistical Analysis : Utilize advanced statistical methods to build robust models, leveraging expertise in R programming.

- Collaboration : Work closely with data scientists, business analysts, and other stakeholders to align models with business needs.

- Continuous Improvement : Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Key Skills :

- Skills highlighted with are preferred keyskills : Python, Predictive Modeling, MLOps, Logistic Regression, Artificial Intelligence, Natural Language Processing, Machine Learning, Fraud detection, Deep Learning, Scikit-Learn, Numpy, Model Development, MLflow, Data Science, R, Linear Regression, Pandas, Statistical Modeling.