Data analyst

Primary Focus:

• 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

Qualifications:

• 1-3 years of experience in data analysis or data science, preferably with exposure to credit risk or the fintech industry.
• 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.
• Bachelor’s degree in a STEM field: Science, Technology, Engineering, or Mathematics.
• English (B2 or higher) is required for internal communication, with Russian (B1 or higher) as a plus.
• Strong analytical and problem-solving skills.
• Experience in a retail banking environment with an understanding of credit risk is a plus.

Working with us means:

• An open atmosphere and vibrant team life without unnecessary bureaucracy or dress code;
• Medical insurance with extended coverage after the probation period;
• Coverage for conference participation, discounts for English language courses, and access to educational platforms (Coursera, Udemy);
• Internal meetups: lightning & thunder talks;
• High-performance equipment and additional monitors for productive work;
• Class “A” office in the city center
• A multicultural team (Georgia, Russia, Poland, Kazakhstan, Kyrgyzstan, Ukraine, Tajikistan);
• Referral program "Bring a Friend" with bonus opportunities;
• Coffee points for snacks at any time;
• Team-building and sports events that foster team spirit.