Description

You will design, develop, and deploy analytics solutions and data infrastructure that support client-advisory workflows and financial decision-making. This role combines data engineering with application development to build scalable, self-service tools for business stakeholders.

This role is on-site.

Responsibilities

• Design and maintain clean, well-modeled datasets and analytics layers that enable business stakeholders to answer their own questions.
• Develop and deploy applications and analytics solutions that make financial data accessible and actionable across the firm.
• Own data quality, documentation, and reliability for analytics products and pipelines, focusing on scalability and self-service.
• Translate business workflows into technically sound solutions, making independent decisions on feasibility, tooling, and architecture.
• Identify and apply emerging AI and analytics technologies to improve financial services workflows.

Required Skills

• 5+ years of data science, analytics engineering, or data-heavy application development experience with a track record of shipping production products.
• Proficiency in Python, Julia, R, or JavaScript/TypeScript.
• Experience with at least one public cloud platform (Azure, AWS, or GCP).
• Strong SQL skills and experience working with data warehouses or analytical data platforms.
• Experience with CI/CD practices and source control tools such as GitHub or Azure DevOps.
• Familiarity with data modeling concepts and transforming raw data into clean, structured datasets.

Preferred Skills

• Familiarity with Azure services such as Azure AI, Function Apps, or Azure OpenAI.
• Experience integrating LLM APIs (OpenAI, Anthropic, Azure OpenAI) into production applications or data workflows.
• Comfort using AI-assisted code generation tools (GitHub Copilot, Cursor) in an active development workflow.

Key Skills

Education

Any Graduate