Middle Data Scientist
- Рівень:
- middle
- Джерело:
- djinni.co
Що робити
- Analyze large-scale transaction datasets to identify fraud patterns and risk signals.
- Develop and validate ML models for risk scoring and fraud detection/classification.
- Support deployment of models into production environments by collaborating with the development team.
- Monitor model performance, conduct regular evaluations, analyze the results.
- Perform feature engineering to continuously improve model performance.
Що очікуємо
- 2+ years of experience working with large-scale, complex datasets.
- Experience with imbalanced data.
- High proficiency in Python for data analysis, feature engineering and modeling.
- Expertise in exploratory data analysis and preparing clean, structured datasets for model development.
- Hands-on experience with AI/ML techniques:
Що пропонуємо
- Hands-on experience in the fraud/risk domain.
- Experience with Databricks (including Pyspark) for data processing, experimentation, and model development.
- Experience in MLflow library for experiment tracking and model lifecycle management.
- Experience working with diverse data sources (e.g., behavioral, device, or transactional data) and deriving meaningful features.
- Experience assessing data quality and validating new data sources in production environments.
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