Vacancy expired!
#6554
Seeking a Data Scientist to join a global AI product support team. This scientist will report to the Senior Director of Global Data Science Products and will play a critical role in the rollout of the global suite of AI products across consumer lending, business intelligence services and health product suite. This role will cover a wide range of responsibilities with plenty of variation from week to week. Responsibilities will include but are not limited to: Product Development- Prototype new modeling methodologies for incorporation into global suite
- Work directly with ML engineering team to identify issues and guide them on requirements
- Write data pipelines / ETL for non-standard or new modeling use cases
- Build new dashboards and reports to provide insights to clients on model performance and impact, leveraging proprietary BI toolkit
- Help document methodologies, tool usage and business logic
- Support client implementation teams executing complex modeling tasks on our enterprise ML ops platform
- Perform complex/custom data engineering where needed to support strategic clients
- Train ML models for underwriting, targeting and other applications where needed
- Test new product features and algorithms and verify accurate implementation ahead of live release to global client base
- Implement bug-fixes and upgrades to methodologies in credit-related business logic (e.g., Bureau Inferencing modifications etc.)
- Highly proficient writing data processing code with at least one SQL dialect
- Spark SQL experience desirable but not required
- Comfortable using Python and Jupyter notebooks with common open source libraries for machine learning
- MLlib, PyTorch, Sklearn, Tensorflow all valuable
- Understanding of credit risk modeling fundamentals
- Strong communication skills - able to talk to business users to understand and articulate issues requirements, as well as more technical developer audiences
- Strong data visualization skills - can present datasets to bring out insights & tell a story
- Self-starter willing to solve problems and ask the right questions, growth mindset
- Desirable: Familiarity with widely-used credit risk assessment tools like FICO Model Builder and SAS
- Desirable: Understanding of the credit risk lifecycle from prospecting and acquisition to customer management and collections
- Experience in modeling and/or data engineering in a Credit Risk institution. You will have worked at least 3 - 5 years for a major bank, FinTech or other financial institution.
- At least 5 - 7 years total industry experience focused on analytics, data science and/or data engineering, with some direct experience in applied statistics and machine learning
- Advanced degrees in quantitative fields and/or professional experience in applied analytics are valuable
- Bachelor's degree required, Master's degree preferred
Vacancy expired!