Job responsibilities
- Utilize cutting-edge approaches to design and develop sophisticated machine learning models to drive impactful decisions for the business
- Leverage big data/distributed computing/cloud computing platforms to optimize and accelerate model development processes
- Work closely with the senior management team to develop ambitious, innovative modeling solutions and deliver them into production
- Collaborate with various partners in marketing, risk, technology, model governance, etc. throughout the entire modeling lifecycle (development, review, deployment, and use of the models)
Required qualifications, capabilities, and skills
- Ph.D. or MS degree in Mathematics, Statistics, Computer Science, Operational Research, Econometrics, Physics, or other related quantitative fields
- Deep understanding of advanced machine learning algorithms (e.g., regressions, XGBoost, Deep Neural Network CNN, RNN and Transformer, Clustering, Recommendation) as well as design and tuning procedures
- Polished and clear communication
Preferred qualifications, capabilities, and skills
- Minimum 4 years of experience in developing and managing predictive risk models in financial industry
- Demonstrated experience in designing, building, and deploying production quality machine learning and deep learning models. Experience in interpreting deep learning models is a plus
- Minimum 4 years of experience and proficiency in coding (Python, Tensorflow or PyTorch, PySpark, SQL), familiarity with cloud services (AWS Sagemaker, Amazon EMR)
- Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is a plus
- Strong ownership and execution, proven experience in implementing models in production
