Vice President Data Scientist (AFC Modelling, Transaction Monitoring)

Join our team as a Vice President Data Scientist, where you will play a crucial role in advancing data science and analytical capabilities within the Financial Crime organization. You will lead the development and implementation of advanced analytics and machine learning solutions, drive data science strategy, and provide technical leadership and mentorship to junior team members. The ideal candidate will have strong programming expertise in Python, experience with large-scale datasets, and a background in financial services or regulated industries.

- Lead the development and implementation of advanced analytics and machine learning solutions supporting Financial Crime and AFC initiatives. - Drive data science strategy by partnering with business, compliance, technology, and risk stakeholders to solve complex problems and deliver actionable insights. - Design, enhance, and monitor predictive models and analytical frameworks using large and complex datasets.

- Strong programming expertise in Python and data science libraries including Pandas, NumPy, and Scikit-learn - Advanced experience working with large-scale datasets, SQL, data modeling, and modern analytics platforms - Proven ability to leverage AI tools to enhance productivity, optimize workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs - Significant experience developing and deploying machine learning, statistical, or advanced analytics solutions within financial services or other regulated industries - Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Systems, or a related quantitative discipline; Master's degree preferred - Strong communication and stakeholder management skills with the ability to influence business and technical audiences at all levels - Experience within Financial Crime, Anti-Money Laundering (AML), Fraud, Compliance, Risk Management, or Regulatory Technology environments - Exposure to Transaction Monitoring, customer risk analytics, sanctions screening, or other financial crime surveillance programs - Experience with Hadoop, Hive, Spark, cloud-based analytics platforms, or other big data technologies - Strong analytical and problem-solving skills with the ability to translate business challenges into scalable solutions - Ability to balance strategic thinking with hands-on execution in a fast-paced and evolving environment