Founding AI Data Scientist

Job Title: Founding AI Data Scientist

Location: Remote (United States)

About The Company

Our client is a leading financial technology (FinTech) software company that provides cloud-based lending and account opening solutions to banks, credit unions, mortgage lenders, and consumer lending organizations throughout North America.

As part of a significant enterprise AI transformation led by executive technology leadership, the organization is investing in building a modern AI platform capable of supporting next-generation AI products, intelligent automation, and enterprise-wide AI initiatives. This newly created position will play a foundational role in helping establish the company's AI data science capability and build the data assets that power enterprise AI.

Job Summary

We are looking for a Founding AI Data Scientist to join the Data Engineering organization in a 100% remote capacity. The ideal candidate is an experienced AI practitioner who enjoys building foundational AI capabilities rather than simply developing predictive models. This individual will operate at the intersection of Data Science, AI Platform Engineering, and Data Engineering while helping establish the organization's AI data foundation.

This role will involve designing AI-ready datasets, building vector stores and feature stores, supporting Retrieval-Augmented Generation (RAG), developing graph data models, partnering with Machine Learning Engineers, and enabling enterprise AI applications. Rather than joining an existing Data Science team, this individual will become the company's first dedicated Data Scientist and help build the foundation for future AI initiatives.

Key Responsibilities

• Build AI-ready data foundations: Design, develop, and maintain curated datasets that support enterprise AI applications, machine learning models, and Retrieval-Augmented Generation (RAG) while ensuring data quality, governance, and scalability.
• Develop modern AI infrastructure: Design and operate vector stores, feature stores, graph databases, embedding pipelines, semantic retrieval systems, and AI-ready data assets that accelerate enterprise AI development.
• Lead data discovery and analytics: Analyze lending, deposit, behavioral, and operational datasets to identify trends, anomalies, business opportunities, and model drivers that support product, risk, and growth initiatives.
• Partner across Engineering and AI teams: Collaborate closely with Data Engineering, Machine Learning Engineers, Product Management, and Software Engineering teams to ensure AI applications consume trusted, production-ready data assets.
• Establish AI best practices: Build evaluation frameworks for retrieval quality, feature quality, embeddings, and AI data governance while helping define the future direction of the organization's Data Science capability.

Requirements

Education:Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related technical discipline required. Master's degree preferred.

Experience:4–7+ years of experience in Data Science, Machine Learning Engineering, Applied AI, AI Platform Engineering, or Data Engineering. Experience building AI-ready data assets consumed by production AI or Machine Learning applications. Experience working within enterprise AI environments supporting production systems.

Skills:Python, SQL, Databricks, Apache Spark / PySpark, Retrieval-Augmented Generation (RAG), Vector Databases, Vector Search, Embeddings, Feature Stores, Semantic Search, Graph Databases (Neo4j, TigerGraph, Azure Cosmos DB Gremlin, or similar), Machine Learning, Large Language Models (OpenAI, Azure OpenAI, Hugging Face, LangChain, or similar), Data Engineering, ETL / ELT, AI-ready Data Pipelines.

Other:Strong communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders. Ability to work collaboratively across Product, Engineering, and Data organizations. Must be authorized to work permanently in the United States without current or future sponsorship.

Preferred Qualifications

• Experience building AI capabilities from the ground up within an enterprise environment.
• Financial Services or FinTech industry experience.
• Experience designing AI platforms or AI data foundations.
• Experience working with enterprise AI architecture and production AI systems.
• Knowledge of prompt engineering, prompt evaluation, and LLM optimization.
• Experience supporting AI governance, responsible AI, and enterprise data quality initiatives.
• Experience working with Azure or AWS cloud environments.

Benefits

Competitive Salary:Competitive base salary commensurate with experience.

Health and Wellness:Comprehensive medical, dental, vision, and additional health benefits.

Work-Life Balance:100% remote work environment with flexible scheduling and generous paid time off.

Professional Development:Opportunity to become the organization's founding Data Scientist and play a critical role in building enterprise AI capabilities while partnering directly with executive technology leadership.

Additional Perks:Opportunity to build foundational AI capabilities from the ground up. High visibility with executive leadership. Work with cutting-edge AI technologies including Databricks, vector databases, feature stores, graph databases, and Retrieval-Augmented Generation (RAG). Significant opportunity to influence enterprise AI strategy and future AI product development.