Junior Data Scientist

at an accredited IT company Pole.rf for two priority projects: a wagon fleet management system and a freight transport tariff forecasting system. Paid internship with mentorship and work on real data.

• Collection and consolidation of data from various sources
• Feature engineering, Survival analysis: Cox PH, Kaplan–Meier, AFT models
• Correct validation, basic baselines, and model interpretation (SHAP, permutation importance, PDP)
• Reproducible pipelines, production monitoring: data drift / concept drift, PSI
• Visualization: dashboards of rate dynamics, heatmaps of routes

• Mathematical or technical education: software engineering, computer science and engineering, applied mathematics and informatics, or related disciplines

• Young specialist with higher technical education or a final-year student of a technical university

• Python, experience with SQL and NoSQL databases

• Principles of supervised learning, regularization, cross-validation, bias-variance tradeoff

• Excellent knowledge of mathematical statistics, ability to build reliable data pipelines, understanding of metrics (MAE, RMSE, MAPE)

• Python

• SQL

• NoSQL

• Survival analysis

• Cox PH

• Kaplan–Meier

• AFT models

• SHAP

• Permutation importance

• PDP

• Data drift

• Concept drift

• PSI

• MAE

• RMSE

• MAPE

• Paid internship for 3–6 months and access to real data
• Work in an accredited IT company, official employment
• Part-time and hybrid format — can be combined with studies
• Mentorship from senior specialists, code review, participation in the full cycle: from hypothesis to production model
• Opportunity to credit the project as practical training, coursework, or thesis