As a Senior Applied Scientist, Credit Risk at ramp, you will be responsible for designing and developing predictive models to assess credit risk. You will leverage machine learning and statistical techniques to analyze large datasets and identify trends and patterns. Your work will have a direct impact on the company's risk assessment and decision-making processes.
Key Responsibilities:
- Design and develop predictive models to assess credit risk, leveraging machine learning and statistical techniques.
- Analyze large datasets to identify trends and patterns, and develop insights to inform business decisions.
- Collaborate with cross-functional teams, including data engineering, product, and risk management, to integrate models into production.
- Develop and maintain high-quality, well-documented code, and ensure compliance with company standards and best practices.
- Stay up-to-date with industry trends and advancements in machine learning and statistical modeling, and apply this knowledge to improve model performance and accuracy.
Requirements:
- PhD in Computer Science, Statistics, Mathematics, or related field, or equivalent experience.
- 5+ years of experience in machine learning, statistical modeling, and data analysis, with a focus on credit risk assessment.
- Strong programming skills in Python, with experience with AWS and related technologies.
- Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.
- Experience with data visualization tools, such as Tableau or Power BI, and ability to communicate complex technical concepts to non-technical stakeholders.