[Remote] Data Scientist, AI Data Foundations

About the role

FlexBoard is looking for a Data Scientist to join our AI Data Foundations team to build the infrastructure that powers our machine learning and AI applications. You will be responsible for creating high-quality data structures, managing feature stores, and designing graph databases to support our digital lending platform.

Key facts

What you'll do

• Architect and maintain vector stores for retrieval-augmented generation, including embedding pipelines, chunking, and indexing strategies.
• Manage feature store assets for offline and online inference, ensuring data freshness and point-in-time correctness.
• Develop graph data structures to map relationships between applicants, products, and lenders for analytical and AI use cases.
• Perform deep-dive data discovery on lending and behavioral datasets to identify trends, anomalies, and potential model drivers.
• Create curated datasets for AI consumption, ensuring proper documentation, governance, and data classification.
• Define evaluation frameworks to measure RAG retrieval performance, embedding quality, and graph completeness.
• Collaborate with ML engineers to ensure data structures effectively support model training and production workflows.
• Translate complex data findings into clear narratives for both technical and business stakeholders through dashboards and reports.

Requirements

• 4 to 7 years of experience in data science, ML engineering, or data roles, specifically focused on building data assets for model consumption.
• Hands-on experience designing vector stores for semantic search or RAG.
• Experience building or operating feature stores, including offline training and online serving patterns.
• Proficiency in graph database modeling and query writing.
• Strong technical skills in Python (pandas, NumPy, scikit-learn, PySpark) and SQL.
• Practical experience deploying embedding models and LLM tooling in production environments.
• Bachelor or Master degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent experience.

Nice to have

• Experience in FinTech, specifically with lending, deposits, credit, fraud, or KYC/AML data.
• Familiarity with AI/ML tools like MLflow, feature stores, and data catalogs.
• Knowledge of vector databases such as pgvector, Chroma, or FAISS.
• Experience with Azure data and AI services, including Azure AI Search and ADLS Gen2.
• Background in evaluating RAG systems using metrics like recall@k, faithfulness, and hallucination measurement.
• Exposure to graph algorithms such as centrality or community detection.

Skills & tools

• Python, SQL, PySpark, pandas, NumPy, scikit-learn
• Vector stores, Feature stores, Graph databases
• LLM tooling, Embedding models, RAG evaluation
• Azure data and AI services

Practical notes

FlexBoard has a history of providing H1B visa sponsorship, though this does not guarantee sponsorship for this specific position. The company is headquartered in Costa Mesa, California, and operates as a digital lending platform founded in 1998.