Senior Data Scientist

Key Responsibilities

• Lead and deliver advanced data analysis, statistical modeling, and machine learning solutions to support credit analytics, risk assessment, credit scoring, and portfolio performance monitoring.
• Design, develop, validate, and continuously improve predictive models related to credit behavior, default risk, fraud indicators, and data quality metrics.
• Perform data exploration, experimentation, feature engineering, and model optimization using Python/R and SQL on large-scale, structured, and sensitive credit datasets.
• Take full ownership of the analytical model lifecycle, including development, deployment, performance monitoring, stability tracking, recalibration, and documentation.
• Ensure high standards of data quality, consistency, confidentiality, and integrity across all analytical processes.
• Translate complex analytical results into clear, actionable insights through reports, dashboards, and visualizations using BI tools such as Power BI or Tableau.
• Act as a strategic data partner to Risk, Product, Business, and Technology teams, supporting credit product development, risk policy formulation, and enterprise analytics initiatives.
• Provide technical guidance and mentorship to junior data scientists and analysts.
• Apply and promote best practices in data governance, data privacy, model governance, and regulatory compliance in alignment with financial services regulations.
• Contribute to the continuous enhancement of data science standards, methodologies, and analytics frameworks within the organization.

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Qualifications

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Data Science, Economics, Engineering, or a related quantitative field.
• Minimum 5 years of relevant experience in data science, advanced analytics, or statistical modeling, with demonstrated senior-level responsibilities.
• Strong hands-on expertise in Python and/or R, SQL, and experience working with large-scale structured datasets.
• Solid understanding of credit risk concepts, including credit scoring, consumer credit behavior, portfolio analytics, or alternative data, preferably within financial services, banking, fintech, or credit bureau environments.
• Proven experience in developing, deploying, and monitoring analytical models in production environments.
• Experience with model governance, documentation, and regulatory or audit review processes in a regulated environment.
• Strong ability to communicate complex analytical insights clearly and effectively to both technical and non-technical stakeholders.
• Ability to work independently, take ownership of analytical outcomes, and provide sound judgment in data-driven decision-making.