Data Scientist

Position Summary

We are seeking a highly capable Data Scientist with approximately three years of experience to accelerate our journey toward data-driven wealth management. In this role, you will partner closely with advisors, investment professionals, and technology teams to unlock insights that enhance portfolio construction, client personalization, and operational performance. This position blends financial domain knowledge with advanced analytics and machine learning, offering an opportunity to influence the evolution of our data ecosystem and the future of our platform.

Primary Responsibilities

• Analyze large, complex financial and client datasets to uncover trends, behavioral patterns, and investment signals.
• Design, validate, and operationalize predictive models to support asset allocation, risk assessment, and client segmentation strategies.
• Collaborate with business and financial stakeholders to translate strategic objectives into analytical approaches and data-driven solutions.
• Build and maintain scalable data pipelines and workflows, ensuring reliable data ingestion, transformation, and quality within Snowflake environments.
• Develop intuitive dashboards, visualizations, and reporting artifacts (Power BI, Tableau, or similar) to communicate insights and influence decision-making.
• Work closely with engineering teams to integrate analytical outputs and models directly into core wealth management systems and workflows.
• Maintain thorough documentation and uphold data governance, controls, and compliance standards aligned with financial regulations and industry best practices.

Qualifications

• Master’s degree in Data Science, Computer Science, Statistics, Finance, or a related quantitative field.
• Hands-on experience in Data Science, ideally within financial services, wealth management, investment analytics, or related sectors.
• Strong programming experience in Python or R for statistical modeling, machine learning, and data manipulation.
• Proficiency in SQL and demonstrated experience with Snowflake for data warehousing and analytical workloads.
• Solid understanding of financial instruments, portfolio construction, performance metrics, and risk modeling concepts.
• Experience with data visualization and business intelligence platforms (e.g., Tableau, Power BI, Looker).
• Familiarity with cloud environments (AWS, Azure, or GCP) and modern data stack components.
• Exceptional communication and stakeholder engagement skills, with the ability to convey complex concepts to non-technical audiences.
• Experience with OpenAI function calling, MCP servers, or custom agent integration
• Experience with Retrieval-Augmented Generation (RAG) and vector database expertise
• Experience working with modern LLMs (OpenAI, Anthropic, Google)