Senior Risk Analyst in Pletin A., FOP

A consumer finance platform for online lending is looking for Senior Risk Analyst.

Key responsibilities:

• Designing, testing, and validating risk models (regression, classification, XGBoost, LightGBM, CatBoost, deep learning).
• Building and maintaining end-to-end data science pipelines: problem scoping, data collection, feature engineering, EDA, model building, validation, tuning, monitoring, and maintenance.
• Writing and optimizing SQL queries to extract and analyze large datasets.
• Applying Python libraries (Pandas, NumPy, SciPy, Scikit-learn, Flask) for statistical analysis, modeling, and deployment.
• Developing dashboards and reports in PowerBI/Excel to provide risk insights and recommendations for management.
• Conducting portfolio monitoring, stress testing, and scenario analysis to evaluate risk exposure.
• Supporting model deployment and integration with IT systems, including Docker or cloud environments (e.g., GCP BigQuery, Dataflow).
• Collaborating with Product, Finance, IT, and Operations teams to ensure risk models align with business objectives.
• Continuously identifying patterns, trends, and emerging risks, and providing
  recommendations to mitigate them.
• Maintaining up-to-date knowledge of best practices in risk management, data science, and machine learning.

Job requirements:

• Bachelor’s degree or higher in Statistics, Mathematics, Computer Science, Data Science, or related fields. ? 
• 2+ years of hands-on experience in data science, data analysis, or risk analytics. ? 
• Strong foundation in probability theory, statistics, discrete mathematics, logic, and algebra. ? 
• Proficiency in SQL and Python (pandas, numpy, scikit-learn, scipy). ? 
• Experience in building models from scratch (problem definition, data collection, feature engineering, model selection, validation, tuning). ? 
• Upper-intermediate English level (written & spoken).

Desired Skills: ? 

• Familiarity with Hadoop ecosystem and NoSQL databases. ? 
• Experience with Docker and ML model deployment. ? 
• Knowledge of financial analysis/credit scoring. ? 
• Exposure to cloud technologies (e.g., GCP BigQuery, Dataflow). ? 
• Experience in advanced ML domains: computer vision, NLP, recommender systems