Posted 6 months ago
We are looking for talented people with deep knowledge of model risk management best practices and a passion for applying Machine Learning / Statistics within the financial services industry.
This position provides the opportunity to help increase the adoption of A.I. within the financial services industry, and drive model risk management best practices for all industries around the world. Your responsibilities will include thought leadership around the automation of model validation best practices, research and development of cutting-edge tools and processes used to validate machine learning models, and delivering novel ways for DataRobot users to detect and effectively manage model risk.
Roles & Responsibilities:
- Help build DataRobot's model risk management capabilities by leading extensive model validation related research & development activities using cutting-edge data science techniques.
- Effectively collaborate cross-functionally with other teams like Sales, Product, and Engineering.
- Help identify sources of machine learning model risk and inspire novel techniques to validate such models.
- Enable customers in the financial services industry to successfully navigate model risk management requirements using DataRobot – including 1st-line-of-defense requirements as well as 2nd-line-of-defense validation efforts.
- Knowledge of Model Risk Management regulations (SR-11-7, OCC 2011-12, etc.).
- 2 - 5+ years experience building and implementing predictive models using machine learning algorithms in the financial services industry (preferred model validation-specific experience).
- Deep understanding of best-practices for effective model validation. Related experience preferred.
- Deep theoretical understanding of Machine Learning
- Fluency with scripting (Python / R) (software engineering experience a plus)
- Excellent verbal and written communication skills are necessary (ability to explain complex ideas in simple, non-technical language)
Individuals seeking employment at DataRobot are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.