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.

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.