I am working with a digital lending company looking for a Senior Data Scientist who will be responsible for building credit and fraud risk models. Candidates should have 4+ years of experience in developing credit models for small business lending along with strong knowledge of machine learning and proficiency in R/Python/SQL.
Responsibilities:
- Manipulate structured and unstructured datasets from disparate sources
- Perform data processing, integration, cleansing, descriptive analysis, visualization, and reporting
- Develop, document, monitor, and improved machine learning models for credit assessment, fraud detection, and other relevant customer lifecycle models
- Performs advanced analytics (statistical and predictive analytics, machine learning modeling, etc.) to provide actionable insights that improve business outcomes and minimize risk
- Apply data analysis and modeling techniques to support business decisions
- Hands on role in deploying models and tracking performance metrics
- Implements projects from inception to completion, managing timelines and resources independently to deliver expected outcomes.
- Engage stakeholders to understanding business requirements (compliance, engineering, product, marketing, etc.)
- Provides consultation to business leaders and other stakeholders on how to leverage analytics insights and build strategies around analytics
Qualifications:
- Degree in a quantitative field such as computer science, engineering, mathematics, statistics, etc. (post graduate degree preferred).
- 4+ years developing credit/fraud models for small business lending
- Fluency in programming languages such as R, Python, SQL.
- Experience developing supervised and unsupervised machine learning algorithms
- Strong programming practices utilizing version control systems (e.g. Git)
Preferred:
- Experience developing advanced models (default prediction, revenue forecasting, response prediction, etc.) in multiple functional areas (credit, fraud, marketing, etc.)
- Extensive experience developing credit models with GBM and Logistic Regression
- Experienced working withing Google Cloud AI tools
- Experience in applying statistical techniques to draw causal inferences in both experimental and non-experimental situations
- Experience leading end-to-end data science projects
- Experience mentoring other data scientists