Principal Data Scientist, SIP

Responsibilities

• check_circle Leading and collaborating with software engineers, data engineers, and investment professionals to build innovative AI-based tools using structured and alternate data sources.
• check_circle Designing and implementing complex reasoning loops using frameworks like LangGraph, LangChain, or AgentCore, transforming static LLMs into dynamic, goal-oriented agents.
• check_circle Developing robust evaluation frameworks and 'gold-standard' datasets to measure the performance, faithfulness, and accuracy of generative outputs.
• check_circle Scaling AI initiatives and agentic development across Invesco Technology teams by creating reusable patterns, prompt templates, agentic harnesses, skills, and subagents with GitHub Copilot and Claude Code.
• check_circle Collaborating with full stack engineers to integrate AI models into business workflows, using AI-assisted coding to move from a notebook experiment to a functional microservice in record time.
• check_circle Implementing systematic testing (e.g., RAG evaluation, stress testing) to ensure AI solutions meet the high compliance and reliability standards of the financial services industry.
• check_circle Applying emerging techniques in prompt engineering, fine-tuning, and multi-agent systems to solve unique business challenges.

Basic qualifications

• 7-10 years of demonstrated experience in data science or machine learning, with a strong emphasis on Natural Language Processing (NLP) and Generative AI.
• Strong foundation in Python and cloud-native development; you write clean, modular code and are comfortable with Docker, CI/CD, and DevSecOps.
• Exposure to or high enthusiasm for learning LangGraph, LangChain, Copilot Studio, or AgentCore with Strands.
• Familiarity with creating evaluation metrics and building datasets for model validation and testing.
• Proactive use of AI tools (GitHub Copilot, Cursor, etc.) to accelerate technical tasks and explore new libraries.
• A desire to work at the intersection of data engineering and full-stack development, with the agility to pivot based on rapid sprint feedback.

Benefits

• check_circle Flexible paid time off
• check_circle Hybrid work schedule
• check_circle 401(K) matching of 100% up to the first 6% with a discretionary supplemental contribution
• check_circle Health & wellbeing benefits
• check_circle Parental Leave benefits
• check_circle Employee stock purchase plan

About the company