We are seeking an Asset Management AI Research Analyst to collaborate directly with our investment teams in developing AI / ML tools to support our fundamental investment research process. This role requires a unique combination of deep quantitative expertise, modern AI/ML techniques, and investment industry work experience. The ideal candidate will bring context to the investment process from both theory and practice. Our team embeds with portfolio managers, investment analysts, trading teams, and partners in risk and compliance to develop AI-powered solutions for our fundamental investment process. The ideal candidate will have experience working with investment data, data engineering, coding, CI-CD frameworks, AI / ML Ops.

REQUIRED QUALIFICATIONS:

• MS/PhD in Financial Engineering, Computer Science, Machine Learning, Physics Mathematics, or related technical field
• Exposure and interest in emerging frameworks including MCP (Model Context Protocol)
• Strong programming skills in Python with extensive experience in ML libraries (PyTorch, TensorFlow, scikit-learn, transformers)
• Proficiency with cloud platforms (AWS, GCP, Azure) and distributed computing frameworks
• Experience with MLOps tools and practices (MLflow, Kubeflow, Docker, CI/CD for ML)
• Knowledge of buy-side workflows from idea generation through trade execution and performance monitoring
• Experience with market and company fundamental data, market microstructure, and alternative data sources
• Experience with data visualization and reporting tools, such as Tableau, DOMO, or power platform (PowerBI and PowerApps).

PREFERRED QUALIFICATIONS:

• Expert proficiency in SQL, Databricks, Snowflake
• Proficient user of financial APIs (Bloomberg, Refinitiv, FactSet) and financial databases in real investment contexts
• Working knowledge of regulatory requirements and compliance considerations in asset management (SEC, CFTC, FINRA)
• Excellent analytical and problem-solving skills, with experience in statistical modeling, regression, and predictive modeling.
• Strong communication and collaboration skills, with the ability to present sophisticated technical ideas to collaborators and team members.
• DevSecOps experience
• CFA Charter or demonstrated progress

When you join our team:

• We’ll empower you to learn and grow the career you want.
• We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
• As part of our global team, we’ll support you in shaping the future you want to see.

LI-Hybrid

• Develop prototype AI solutions in partnership with equity, fixed income, multi-asset, and private markets investment teams.
• Design and implement large language model (LLM) powered applications for financial document analysis, earnings call transcription processing, and research report generation
• Build natural language processing pipelines for extracting insights from unstructured financial data (10-Ks, earnings transcripts, news, analyst reports)
• Develop retrieval-augmented generation (RAG) systems for financial research and knowledge management
• Create AI-powered research assistants that can synthesize information across multiple data sources and investment frameworks
• Implement explainable AI frameworks to ensure model transparency and regulatory compliance
• Develop graph neural networks for analyzing company relationships, supply chains, and market interconnections
• Build sentiment analysis models specifically tuned for financial communications and market data