Job Responsibilities-
- Apply analytical, data science, and machine learning skills to solve complex business problems.
- Work across teams to design, develop, and implement analytical models.
- Responsible for these models throughout the model’s life cycle, including data cleanup, data analysis, model selection, ongoing performance monitoring, issue resolution, and model retirement.
Required qualification, capabilities and skills-
- Ph.D. or Master’s degree from an accredited university in a quantitative field such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering
- Demonstrated experience in designing, building, and deploying production quality machine learning models.
- 3+ years of relevant analytics experience
- Extensive practical expertise and work experience with Machine Learning, both supervised and unsupervised.
- Excellent programming skills using Python/SAS and/or R, Spark, Hive, SQL.
- Familiarity with standard data science tooling and good understanding of algorithms and software engineering fundamentals.
- Excellent problem solving, communications, and teamwork skills.
Preferred qualification, capabilities and skills-
- Experience with credit risk modeling and analytics such as scorecard or loss forecasting models.
- Extensive experience with design and deployment of AI/ML models with modern data science techniques such as XGBoost, Neural Networks.
- Experience in working with engineering teams to operationalize Machine Learning models.