Віддалена робота
Senior Risk Analyst
Віддалена робота
Гібридна
В офісі/на місці
Повна зайнятість
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
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