Job Description

We're seeking a skilled Consumer Risk Business Analyst to join our team. The ideal candidate will possess strong analytical skills, excellent communication abilities, and a deep understanding of business operations and risk management. This role involves analyzing data to identify trends, patterns, and insights that inform business decisions, developing and documenting business process models, and proposing technical and process solutions to meet business needs.


Candidate should have a strong background in data analytics, be proficient in Python and its data-related libraries and have experience with version control systems like GitHub. He/She will be responsible for managing and optimizing retail credit processes, ensuring efficient operations, while maintaining high standards of credit risk management

Qualifications:

Education: Bachelor's degree in Business Administration, Information Technology, or a related field

Experience:

Experience with machine learning and predictive analytics to enhance decision-making capabilities.


Familiarity with regulatory requirements and compliance in retail credit.


Proficient in decision management system tools and platforms (e.g., SAS Decision Management, IBM Operational Decision Manager, FICO Decision Management Suite, Oracle Policy Automation).


Strong understanding of business rules management and decision modeling techniques (e.g., DMN, BPMN).


Knowledge of industry best practices in decision management and business process automation.


Proven experience in retail credit management, credit analysis, or a similar role.


Experience with process improvement and optimization in a financial services environment.

Technical Skills:

Proficient in Python and its data-related libraries (Pandas, NumPy, SciPy).


Strong experience with data visualization tools (Matplotlib, Seaborn, Plotly).


Familiarity with machine learning libraries (Scikit-learn, TensorFlow, Keras).


Experience with version control systems (Git, GitHub)


Experience with data integration tools and technologies (e.g., SAS DI Studio, SAS EG, SAS Data flux, SAS VA, ETL, SQL, APIs).

Analytical Skills:

Strong analytical and problem-solving skills, with the ability to translate complex business requirements into effective decision models.


Experience in data analysis and statistical methods to support decision-making processes.


Attention to detail and a thorough understanding of credit risk assessment and management.

Communication Skills:

Excellent written and verbal communication skills, with the ability to explain technical concepts to non-technical stakeholders.


Strong presentation skills and experience in creating detailed technical documentation.