Data Analyst

Key Responsibilities:

• Develop and maintain Python applications that support the credit decision process, including data analysis, scoring models, and reporting tools.
• Collaborate with data scientists and analysts to integrate machine learning algorithms into credit assessment models.
• Utilize statistical methods to analyze large datasets, identifying trends and patterns that influence credit decisions.
• Conduct hypothesis testing and statistical modeling to validate credit risk models and ensure their robustness.
• Optimize existing code and applications for performance and scalability.
• Create and maintain documentation for code, processes, and systems to ensure transparency and knowledge sharing.
• Create visualizations and reports to communicate findings and insights to stakeholders clearly.
• Work closely with cross-functional teams to understand requirements and deliver solutions that meet business needs.

About the Role:

This is a challenging and rewarding opportunity for a skilled data scientist to join our team at HR POD - Hiring Talent Globally. As a data scientist, you will be responsible for developing and maintaining Python applications that support the credit decision process, including data analysis, scoring models, and reporting tools.

Requirements:

• Bachelors degree in Computer Science, Data Science, Statistics or a related field.
• Strong understanding of statistical concepts, including regression analysis, hypothesis testing, and time series analysis.
• Proficiency in Python and familiarity with libraries such as Pandas, NumPy, and scikit-learn.
• Experience with SQL and database management (PostgreSQL).
• Understanding of credit scoring models and financial analysis.
• Solid mathematical background, with the ability to apply mathematical concepts to solve complex problems.
• Strong analytical skills, attention to detail and ability to work independently and collaboratively in a fast-paced environment.
• Experience with cloud computing platforms (e.g., AWS) for data processing and storage is preferred.
• Familiarity with data visualization tools (e.g., Tableau, Python notebooks) is preferred.
• Knowledge of regulatory compliance in the financial industry is preferred.