Principal Data Scientist

Softcard (acquired by Google)

Principal Data Scientist responsible for building AI-based financial tools at Invesco. Leading collaborative efforts in AI initiatives and complex data challenges across technology teams.

Posted 7/18/2026full-timeAtlanta • Texas • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Natural Language Processing (NLP) and Generative AI, with a strong foundation in Python and cloud-native development. Capable of leading AI initiatives, implementing evaluation frameworks, and collaborating effectively across teams to integrate AI solutions into business workflows.

Highest-signal resume keywords

Natural Language Processing (NLP)Generative AIPython ProgrammingCloud-Native DevelopmentAI Tools Utilization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceMachine LearningEvaluation Metrics CreationModel ValidationPrompt EngineeringFine-TuningMulti-Agent SystemsClean Code PracticesDockerCI/CD

Soft Skills

CollaborationProactive Problem SolvingAgility

Tools & Technologies

LangGraphLangChainAgentCoreGitHub CopilotClaude CodeCursor

Industry Keywords

Financial ServicesCompliance StandardsAI SolutionsData EngineeringFull-Stack Development

Tech Stack

Tools & technologies

CloudDockerPython

About the role

Key responsibilities & impact

Leading and collaborating with software engineers, data engineers, and investment professionals to build innovative AI-based tools using structured and alternate data sources.
Designing and implementing complex reasoning loops using frameworks like LangGraph, LangChain, or AgentCore, transforming static LLMs into dynamic, goal-oriented agents.
Developing robust evaluation frameworks and "gold-standard" datasets to measure the performance, faithfulness, and accuracy of generative outputs.
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.
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.
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.
Applying emerging techniques in prompt engineering, fine-tuning, and multi-agent systems to solve unique business challenges.

Requirements

What you’ll need

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

Comp & perks

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