Lowongan Data Scientist 29 Lowongan

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.

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.