Vp, Data Scientist, Group Legal, Compliance

Business Function
Group Legal, Compliance & Secretariat ensures that the bank's interests are protected by zealously guarding and enhancing its reputation and capital. We also work to maintain good standing with all our regulators, customers, and business partners. Because we believe that at the heart of business banking is to uphold the values of trust and integrity for all our stakeholders.
Job Purpose

**Responsibilities**:

- Own and execute machine learning products and initiatives regionally for Group LCS.
- Conceptualise, plan, develop, and deliver relevant analytics models and innovative solutions in Financial Crime, Legal and Compliance, such as Anti-Money Laundering Networks, Transaction Monitoring, Fraud Prevention, Money Mule detection, and Sanctions Screening.
- Partner with domain experts and data scientists from cross-functional teams to drive projects.
- Condense analysis into actionable insights for informed decision-making, strategy development and formulation of standards to enhance business performance and operations at LCS.
- Ensure adherence to the bank’s governance policy and best practices in AI/ML industrialisation, including but not limited to code review, creation and adoption of reusable assets, active adoption of bank’s AI protocol, data governance, post-deployment monitoring, and regular technical / audit / business review of the solution.
- Provide guidance and mentorship to junior team members.

**Requirements**:

- Degree with a strong focus in machine learning, data mining, or statistical / mathematical modelling with deep theoretical knowledge.
- 8+ years of relevant working experience, preferably the most recent 5+ years were on hands-on development of data analytics or AI/ML solutions.
- Familiar with analytics and machine learning platforms and how it integrates with upstream and downstream data and production systems.
- Hands-on experience in end-to-end data science projects covering problem formulation, exploratory data analysis, ML modelling, production deployment, monitoring and production support.
- Familiar with developing machine learning pipelines following dev practice such as versioning, branching, merging, linting, testing and writing codes in a structured and modularized way.
- Able to analyse business needs, and articulate the solution framework, including the model output, business decision and potential impact to drive the adoption of the solution.
- Comfortable working on complex problems, with experience delivering solutions that work under the business or technical constraints, using cutting-edge tools in an agile environment.
- Good presentation and communication skills. Able to explain technical concepts and solutions to a non-technical audience.
- Technical skills: Python, PySpark, SQL, libraries and tools for ML, data visualisation and dashboard, practical experience with cloud platforms.
- An understanding of the legal and compliance issues of complex banking organizations will be a plus.