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Job Description
- Work closely with technical and business teams to provide data insights and contribute to the technology stack
- Implement algorithms for pulling, cleaning, processing and validating structured & unstructured datasets.
- Do proof of concepts (POC) analysis and present results in a clear manner.
- Develop custom data models and algorithms to apply to data sets.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Select features, building and optimizing models using machine learning techniques.
- Develop machine learning techniques and statistical models to solve different problems: time series analysis, customer segmentation, recommendation systems and credit scoring.
Job Requirements
- B.Sc. in Statistics, Mathematics, Computer Science, or another quantitative field.
- 2-4 years of experience handling data sets and building statistical/machine learning models in a production environment
- Experience in communicating with non-technical users
- Experience with time series, recommendation engines, credit scoring, and classification problems
- Experience in Python, SQL, R or other programming languages.
- Understanding of statistics (e.g., hypothesis testing, statistical inference, regression).
- Excellent written and verbal communication skills for coordinating across teams.
- A drive to learn and master new technologies and techniques.
- Preferably a background in software development.