Data Scientist (Private Wealth Management)

Responsibilities

• Formulate and implement the Asset and Wealth Management analytics strategy to drive organizational goals.
• Leverage big data, machine learning, artificial intelligence, and advanced analytics to uncover profound insights in areas like fraud prevention (including early risk alerts and anti-money laundering), alongside marketing and revenue optimization efforts.
• Collaborate with business units and stakeholders to identify requirements, then recommend innovative, data-centric approaches to address them.
• Design and deploy rapid prototypes to demonstrate potential benefits, followed by scaling them into robust production systems for informed decision-making.

Skills Reqd

• Bachelor's or Master's degree in Computer Science, Finance, Business Analytics, or a closely related field.
• Brings 3-5 years of hands-on experience developing data analytics and modeling solutions, ideally within Private Wealth Management or a similar high-net-worth client environment.
• Demonstrates an entrepreneurial, self-driven mindset with strong curiosity for data exploration, capable of independently translating complex data into actionable business insights and strategic recommendations.
• Solid understanding of the private wealth management sector, combined with deep technical expertise in natural language processing (including Transformer architectures), recurrent networks (LSTM), clustering techniques (K-Means), tree-based ensemble methods (Random Forest, Isolation Forest, Gradient Boosting), as well as strong proficiency in SQL, machine learning workflows, and Python programming.