Data Scientist II – Credit Strategy & Risk

Remotedxb; Dubai; On-site; AED 180,000 - 300,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Telemedicine

Meal vouchers

Daycare support

Life insurance

Transport allowance

Job summary

Remotedxb in Dubai seeks a skilled data scientist to develop predictive models for credit risk, churn, and revenue. You will build robust features and scalable data pipelines while ensuring model quality and business impact.

You will use Python and leading ML libraries to deliver actionable insights, validate models, and report progress clearly to stakeholders. The role emphasizes collaboration with analytics and engineering teams in a dynamic environment.

Qualifications

• Experience in developing predictive models with ML and statistics.
• Solid foundation in validation, calibration, discrimination and model stability.
• Proficiency in Python and ML libraries (Scikit-learn, XGBoost/LightGBM, Pandas).
• Clear and proactive communication to report progress and present results.

Responsibilities

• Develop, implement, and evolve predictive models for credit risk, churn, propensity, and revenue using ML and statistics.
• Build and evolve features for models, transforming raw data into relevant, reusable, and reliable variables.
• Build reproducible data pipelines by writing clean and reliable code.
• Define and monitor model quality metrics such as KS, AUC/Gini, precision, recall, uplift, and business impact.

Skills

Predictive modeling

Statistics foundation

Python programming

Communication

Tools

Scikit-learn

XGBoost/LightGBM

Pandas

Spark

Databricks

BigQuery

Job description

Remotedxb in Dubai seeks a skilled data scientist to develop predictive models for credit risk, churn, and revenue. You will build robust features and scalable data pipelines while ensuring model quality and business impact.

You will use Python and leading ML libraries to deliver actionable insights, validate models, and report progress clearly to stakeholders. The role emphasizes collaboration with analytics and engineering teams in a dynamic environment.