Data Science
Machine Learning (ML)
Python- Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
- Implement data pipelines, new features, and algorithms that are critical to our production models
- Create scalable strategies to deploy and execute your models
- Write well designed, testable, efficient code
- Identify valuable data sources and automate collection processes.
- Undertake to preprocess of structured and unstructured data.
- Analyze large amounts of information to discover trends and patterns.
Requirements:
- 2+ years of experience in applied data science or engineering with a focus on machine learning
- Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor, etc)
- strong quantitative and programming skills with a product-driven sensibility
Shubham Vishwakarma
Full Stack Developer - Averlon
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Full Stack Developer - Averlon