Senior Manager
2 days ago
Responsibilities:
- Large data management, feature engineering, strong hands on in EDA and feature Engineering using bureau data in banking domain
- Good to have - Design, implement, and optimize sophisticated machine learning models in Banking domain for Credit Risk modeling.
- Create Python classes and functions to automate EDA and Feature Transformation process
- Stay updated on the latest machine learning advancements, actively identifying and integrating cutting-edge techniques to continuously improve our models and address diverse analytical use cases.
- Provide data-driven insights and recommendations that support decision-making processes and enable us to overcome analytical hurdles.
- Document your methodologies, experiments, and results in clear and concise terms. Effectively communicate complex concepts and findings to both technical and non-technical stakeholders.
Qualifications:
- 4 - 10 years of experience in credit risk analytics preferably in Banking and Financial Services
- A minimum of 3 years of hands-on experience working on Machine Learning models to solve analytical use cases.
- Experience with bureau data feature engineering
- Excellent problem-solving and analytical skills, with the ability to work on complex projects and deliver high-quality results.
- Proficiency in Python programming languages is must
- Experience with large-scale data processing and distributed computing frameworks is a plus.
- Strong communication skills, both written and verbal, with the ability to convey complex ideas to diverse stakeholders
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