Amount is looking to enhance its fraud and risk decisioning platform by developing, selecting, and optimizing machine learning models. The goal is to improve fraud prevention capabilities, optimize underwriting rules, and maximize client product performance in lending and onboarding.
Requirements
- Proficiency in Python and SQL for data manipulation, modeling, and analysis.
- Hands-on experience developing, validating, and implementing machine learning models (e.g., Logistic Regression, Gradient Boosting, Random Forest, Neural Networks).
- Familiarity with decision tree analysis and its application in a business context.
- Experience working with large-scale datasets and cloud-based data platforms (e.g., AWS, GCP, Azure).
- Familiarity with model validation best practices and regulatory requirements in the financial industry.
Responsibilities
- Oversee the entire lifecycle of our proprietary models, including monitoring their performance, identifying areas for improvement, and implementing enhancements with advanced machine learning algorithms.
- Lead the evolution of our core fraud prevention capabilities via our fraud models.
- Conduct build vs. buy analyses, and assessing third-party fraud models to determine the optimal path forward for Amount and its clients.
- Ensure that all models are governed appropriately and serve as a subject matter expert when interacting with our customers regarding models.
- Work closely with our Policy Optimizer product, leveraging statistical methods to help clients configure their credit policies, optimize underwriting rules, and improve key performance indicators.
- Partner with Product, Engineering, and Customer Success teams to ensure our models are effectively integrated, performing as expected, and delivering maximum value to our clients.
- Proactively analyze large datasets to uncover trends, identify new risks, and discover opportunities for product innovation and performance improvement.
Other
- 7+ years of professional experience in a data science role, with a strong emphasis on credit and/or fraud risk management within the financial services or fintech industry.
- A deep understanding of statistical concepts and the ability to apply them to solve complex business problems.
- Excellent verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences, including clients and internal stakeholders.
- You are a strategic thinker who is comfortable with ambiguity and can navigate complex challenges independently.
- Previous experience in a client-facing or consulting role.
