Data analyst

Responsibilities:

• Data Preparation and Analysis:
  • Work with complex datasets, performing data wrangling, cleaning, and preparation tasks.
  • Conduct ad-hoc analyses to uncover insights and answer key business questions related to credit risk.
  • Collaborate with senior team members to prepare data for model development.
• Model Development and Evaluation:
  • Support senior data scientists in developing, testing, and refining ML models, such as application and collection scorecards.
  • Help monitor model performance, track key metrics, and participate in model tuning and optimization efforts.
• Stakeholder Collaboration:
  • Collaborate with a variety of stakeholders, including risk managers, data engineers, and MLOps specialists, ensuring data and model needs are met across functions.
  • Interpret analytical findings and contribute to discussions, helping communicate results to non-technical stakeholders.
• Feature Engineering:
  • Participate in building and maintaining the feature store, contributing ideas and insights to enhance model quality and effectiveness.
  • Support feature engineering efforts, preparing data that will improve model inputs.
• Professional Development:
  • Work closely with senior data scientists, enhancing your skillset and developing expertise in credit risk modeling.
  • Assist junior data analysts as needed, contributing to a collaborative and growth-oriented team environment.

Requirements:

• Experience:
  • 1-3 years of experience in data analysis or data science, preferably with exposure to credit risk or the fintech industry.
• Technical Skills:
  • Proficiency in Python and SQL, with experience using libraries such as Pandas, NumPy, Seaborn, Matplotlib, and Scikit-learn.
  • Familiarity with tree-based algorithms (e.g., XGBoost) and Logistic Regression.
  • Experience in preparing and analyzing large datasets for ML model development.
• Educational Background:
  • Bachelor’s degree in a STEM field: Science, Technology, Engineering, or Mathematics.
• Language Skills:
  • English (B2 or higher) is required for internal communication, with Russian (B1 or higher) as a plus.
• Additional Skills and Knowledge:
  • Strong analytical and problem-solving skills.
  • Experience in a retail banking environment with an understanding of credit risk is a plus.