Data Scientist-Credit Cards

We are seeking a highly skilled Data Scientist with a strong background in the credit card domain to join our dynamic team in Dubai. This is an exciting opportunity to work onsite with a fast-paced and growing startup, where you will leverage your expertise in Python, SAS, and advanced analytics to drive impactful business decisions. You will play a pivotal role in analyzing large datasets, developing predictive models, and delivering actionable insights to stakeholders across product, risk, and marketing teams.

Responsibilities
- Develop and implement statistical models and machine learning algorithms using Python and SAS.
- Analyze large datasets related to credit card usage, fraud detection, customer behavior, and risk modeling.
- Work closely with cross-functional teams including product, risk, and marketing to deliver data-driven insights.
- Perform data extraction, cleaning, transformation, and visualization to prepare datasets for analysis.
- Design and evaluate A/B tests to support product and marketing decisions.
- Build and maintain dashboards, reports, and presentations to communicate findings effectively to stakeholders.

- Apply statistical modeling techniques such as regression, decision trees, and clustering to solve business problems.
- Utilize SAS (Base, Macro, Enterprise Miner) and Python libraries (Pandas, NumPy, scikit-learn) for advanced analytics.
- Conduct customer segmentation analysis to identify patterns and trends in credit card usage.
- Collaborate with risk teams to enhance credit risk analytics and collections strategies.
- Stay updated with the latest advancements in data science, machine learning, and analytics tools.

Requirements
- 5+ years of hands-on experience in Data Science or Advanced Analytics.
- Proficient in SAS (Base, Macro, Enterprise Miner) and Python (Pandas, NumPy, scikit-learn, etc.).
- Strong background in the credit card domain, including risk analytics, collections, and customer segmentation.

- Solid understanding of statistical modeling techniques (e.g., regression, decision trees, clustering).
- Experience working with large-scale structured and unstructured datasets.
- Familiarity with SQL for data querying and manipulation.
- Strong communication and stakeholder management skills.
- Preferred qualifications
- Experience in financial services or banking analytics.
- Knowledge of cloud platforms (AWS/GCP/Azure) is a plus.
- Masters/Bachelors degree in Statistics, Computer Science, Economics, or related field.