Senior Data Scientist

Who you are

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative discipline, or equivalent relevant experience
• Hands-on experience developing applied Data Science or machine learning solutions using Python and SQL, including work with complex datasets and relevant analytical libraries or frameworks
• Demonstrated product thinking and stakeholder management, with the ability to work directly with product users, understand customer needs and product enhancement opportunities, and translate them into practical technical solutions
• Strong foundation in machine learning, statistics, and analytical problem-solving, with the ability to communicate technical concepts and analytical findings to nontechnical stakeholders
• Experience developing, testing, deploying, or supporting machine learning solutions in a production or enterprise environment, with working knowledge of the software development lifecycle, version control, testing, and deployment practices
• 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
• Experience with Google Cloud Platform; strong experience with another cloud environment, such as Microsoft Azure or Amazon Web Services, will also be considered
• Experience applying generative AI or large language models to practical business use cases
• Prior experience in Financial Services, Financial Crime, transaction monitoring, Wealth Management, or another regulated environment
• Experience with model monitoring, data pipelines, MLOps, APIs, or other capabilities used to operationalize analytical solutions
• A proactive, consultative approach to collaboration, innovation, knowledge sharing, and continuous learning

What the job involves

• Serve as a key Data Science partner to U.S. product users and business stakeholders, proactively understanding customer needs, how analytical products are used, and opportunities for product enhancements
• Translate business and customer needs into clear technical requirements and practical Data Science, machine learning, and AI solutions
• Lead the end-to-end implementation of machine learning and AI use cases, from requirements gathering and data identification through model development, testing, validation, deployment, and go-live
• Develop, improve, and support machine learning solutions for AI-driven transaction monitoring and Wealth Management analytics, while evaluating practical generative AI opportunities
• Analyze complex business and customer activity data to identify trends, improve analytical outputs, and generate actionable insights
• Work closely with a global Data Science team and cross-functional partners to deliver solutions efficiently in response to evolving product, business, and regulatory needs