Intern for Sber's "Segments" team, focusing on ML models for customer churn analysis. Participation in the full cycle of DS product creation under mentor supervision.
Tasks:
- Assist in the development and training of customer behavior prediction models
- Conduct exploratory data analysis (EDA): identify patterns, anomalies, and insights to form hypotheses
- Participate in hypothesis generation and business idea testing
- Develop data processing pipelines (under mentor supervision)
- Prepare model code for production deployment and participate in integrating solutions into company platforms
- Evaluate model quality from both a technical (metrics) and business (product impact metrics) perspective
Requirements:
- Basic Python knowledge: confident command of syntax, writing clean code, familiarity with pandas, numpy
- Mathematical foundation: understanding of statistics, probability theory, and linear algebra fundamentals, knowledge of hypothesis testing principles (A/B tests)
- ML: understanding of classic algorithms (linear regression, decision trees, gradient boosting), basic familiarity with Scikit-Learn and LightGBM frameworks
- SQL: ability to write queries for data extraction and aggregation
Conditions:
- Paid internship
- Internship duration: 3 months
- Work schedule: 40 hours per week
- On-site format
- Comfortable modern office
Skills:
- Python
- pandas
- numpy
- SQL
- Scikit-Learn
- LightGBM
- Spark
- PySpark
- Hadoop
- PyTorch
- Git
- CI/CD
