Data Analyst- Feature Engineering- 5-9+yrs- Gurgaon/Bangalore

About the Role

We are looking for highly skilled Data Analyst with strong experience in Python, Bureau Data, and Feature Engineering, preferably within the banking and credit risk domain. The role involves working on large-scale data transformation and feature engineering projects, with an opportunity to contribute to data-driven decision-making and model development for global banking clients.

Location:

Key Responsibilities

• Perform data extraction, cleaning, transformation, and analysis using Python and SQL.
• Work extensively on Bureau data, deriving insights and building engineered features for risk and credit modelling.
• Partner with business and analytics teams to define data requirements and ensure data quality and consistency.
• Design and implement robust data pipelines and transformations for model development and monitoring.
• Support the development of predictive models and risk analytics solutions; experience in machine learning preferred.
• Present analytical findings and recommendations to senior stakeholders.
• Ensure best practices in coding, data validation, and documentation.

Key Skills & Competencies

• Strong Python programming skills with hands-on experience in data analysis and transformation.
• Advanced SQL for querying and managing large datasets.
• Proven experience with Bureau data (e.g. CIBIL, Experian, Equifax) and feature engineering techniques.
• Solid understanding of banking and credit risk domain (retail or commercial).
• Exposure to risk modelling and machine learning concepts.
• Strong analytical thinking, problem-solving, and attention to detail.
• Excellent communication and stakeholder management skills.

Good to Have

• Experience with statistical or ML libraries (e.g., pandas, scikit-learn, numpy).
• Familiarity with data visualization tools (Power BI, Tableau, etc.).
• Understanding of model governance and regulatory requirements in the banking sector.

Why Join Us

• Opportunity to work with global banking and financial clients.
• Exposure to end-to-end analytical proble solving in a fast-paced environment.
• Collaborative, data-driven culture with strong emphasis on learning and growth.