We are looking for a self-motivated, naturally curious person interested in solving complex lending issues in new and innovative ways. This individual must utilize expertise to query, design and translate complex data analysis into simple, user-friendly mediums that are easily digestible by business units and stakeholders. Candidates must be comfortable working on a team and have strong communication and presentation skills.
We are looking for a self-motivated, naturally curious person interested in solving complex lending issues in new and innovative ways. This individual must utilize expertise to query, design and translate complex data analysis into simple, user-friendly mediums that are easily digestible by business units and stakeholders. Candidates must be comfortable working on a team and have strong communication and presentation skills.
Responsibilities :
- Apply best practices and progressive delivery techniques to maintain and monitor a continuously operating production system.
- Build data pipelines by gathering, cleaning, and validating datasets. Establish data lifecycle by using data lineage and provenance metadata tools.
- Maintain and optimize a mission-critical production environment driven by complex business logic and ML; responsible for full-stack system diagnostics, deep-dive root cause analysis, and ensuring robust deployment standards.
- Establish a strategy or model baseline, address concept drift, and prototype how to develop, deploy, and continuously improve a productionized ML application.
Requirement :
- Bachelor's or Master's Degree in Computer Science, Operations Research, Engineering, or related quantitative discipline.
- 1-3 years of experience in programming languages such as Python and SQL.
- 1+ years of hands-on experience in building & implementing AI/ML solutions.
- Experience with python libraries - Numpy, scikit-learn, Pandas, OpenCV, Tensorflow, PyTorch.
- Experience with source version control (Git, Bitbucket).
- Proven knowledge on API Consumption, Docker, Google Big Query.
- Strong analytical skills and data-driven thinking
- Strong understanding of quantitative analysis methods in relation to financial institutions.
- Ability to clearly communicate modeling results to a wide range of audiences.
It is great if you have
- Experience in image processing, OCR (Optical Character Recognition)
