Vice President - Data Science

Responsibilities :

- Design, develop, and deploy end-to-end machine learning and data science models for fraud detection and financial crime mitigation.

- Collaborate with Financial Crime stakeholders to define use cases and identify high-impact opportunities.

- Automate and optimize fraud detection processes through data-driven solutions.

- Analyze structured and unstructured data to develop insightful features and predictive models.

- Present actionable insights and recommendations to both technical and non-technical stakeholders.

- Ensure high-quality documentation, model validation, and compliance with internal governance standards.

- Contribute to the continuous improvement of analytics frameworks and tools.

- Stay updated on emerging trends and technologies in fraud detection and financial crime analytics.

- Proven experience building and deploying machine learning models in a production/business environment.

- Strong analytical mindset and attention to detail with a proactive problem-solving approach.

- Solid foundation in statistical modeling and applied mathematics.

- Excellent communication and collaboration skills across cross-functional teams.

- Ability to effectively explain complex data concepts to non-technical audiences.

- Strong project management and task ownership skills.

- Languages & Tools : SQL (Oracle, Redshift, AWS Glue), Python, Spark, EMR, R/SAS.

- Version Control : Git, GitHub.

- Visualization Tools : Superset, Power BI, Tableau.

- Cloud Platforms : AWS (preferred), Databricks, Azure, GCP.

- Experience with data sourcing, cleansing, ETL processes, and large-scale data engineering pipelines.

- 10+ years of experience in advanced analytics or data science roles.

- Demonstrated experience in the fraud or financial crime analytics domain.

- Experience working with complex datasets (structured and unstructured).

- Ability to derive business value from analytical solutions.

- Track record of delivering insights and solutions that influence key business decisions.

- Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.