Job Overview
Location
US Remote
Job Type
Full-time
Category
Data Science
Date Posted
May 8, 2026
Full Job Description
đź“‹ Description
- • As a Data Scientist in AI Data Foundations at MeridianLink, you will design and build the curated data structures that power AI and ML applications across the company, ensuring high-quality, well-governed data for model training and inference.
- • You will own and maintain vector stores for RAG systems, build and operate feature stores, design graph databases to model complex relationships, and lead data discovery efforts to uncover actionable insights from lending and account-opening data.
- • Reporting into the Data Engineering organization, you will partner closely with ML engineers, applied scientists, and cross-functional teams to ensure data assets accelerate model development and support responsible AI use.
- • This role offers the opportunity to deepen expertise in modern AI data infrastructure, including vector databases, feature stores, and graph technologies, while contributing to scalable, production-grade data solutions in a FinTech/SaaS environment.
🎯 Requirements
- • 4–7 years of experience in data science, ML engineering, or applied data roles, with a focus on building data assets consumed by others’ models or applications.
- • Hands-on experience designing and operating vector stores for RAG or semantic search, including embedding generation, chunking, indexing, and retrieval evaluation.
- • Experience building or operating a feature store (e.g., Databricks Feature Store, Feast, or custom platforms), including offline training, online serving, and point-in-time correctness.
- • Experience modeling and building graph data structures using Neo4j, TigerGraph, Azure Cosmos DB Gremlin, or similar, and writing graph queries to answer real business questions.
- • Strong proficiency in Python (pandas, NumPy, scikit-learn, PySpark) and SQL, with comfort working in Databricks notebooks and jobs.
- • Practical experience with embedding models and LLM tooling (e.g., Hugging Face, OpenAI/Azure OpenAI APIs, LangChain) in production or near-production settings.
🏖️ Benefits
- • Opportunity to work on cutting-edge AI data infrastructure, including vector stores, feature stores, and graph databases, in a real-world FinTech/SaaS context.
- • Collaboration with ML engineers and applied scientists to enable faster, more reliable model development through high-quality data foundations.
- • Exposure to a modern data and AI stack on Microsoft Azure, including Databricks, Delta Lake, Unity Catalog, and Azure AI services.
- • Ability to influence responsible AI practices by partnering with governance, security, and compliance teams on data classification and regulatory adherence.
- • Clear path for growth in AI data engineering and data science, with emphasis on building scalable, production-ready data systems.
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About MeridianLink, Inc.
MeridianLink provides cloud-based software for banks, credit unions, and mortgage lenders to manage loan origination, account opening, credit reporting, and deposit products. The platform automates underwriting workflows, integrates with credit bureaus and core banking systems, and offers analytics for risk management and regulatory compliance. Customers use the APIs and configurable modules to streamline consumer, small-business, and mortgage lending operations while ensuring data security and audit standards.
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