[Remote] Data Scientist

Note: The job is a remote job and is open to candidates in USA. Terzo is an innovative company that builds an AI-native enterprise data platform designed for modern companies. As a Data Scientist on the Applied Research team, you will develop intelligent systems for data extraction and classification, manage model pipelines, and collaborate with engineering and product teams to ensure high-quality outcomes.

Responsibilities

• Build the intelligent systems that create the data our customers depend on
• Design extraction and classification models that process enterprise-scale document corpora
• Build and evolve the entity resolution and signal detection layers powering the Commercial Graph and Financial Graph
• Define how AI capabilities surface as recommendations, agents, and search across the platform
• Own the models, pipelines, and graph structures that are the product
• Work directly with engineering, product, and customers on problems where a single clause can represent tens of millions of dollars of exposure and where model accuracy has a contractual SLA

Skills

• 5+ years of experience in data science, applied ML, or AI research with production-shipped systems, not just notebooks and prototypes
• Strong statistical foundations and the ability to define and evaluate success metrics for AI systems including precision, recall, coverage, latency, not just accuracy
• Deep experience building NLP, NLU, or document understanding models that operate on messy, real-world unstructured data at scale
• Strong intuition for entity resolution, knowledge graph construction, or graph-based modeling and you've thought seriously about how to connect fragmented data into structured, queryable representations
• Hands-on proficiency in Python and modern AI frameworks, with experience deploying models into production pipelines
• Comfort with information extraction, classification, and retrieval-augmented generation patterns applied to real enterprise workloads
• A track record of working cross-functionally with engineering and product to shape what gets built, not just executing on handed-down specs
• Clear, structured communication where you can explain a model decision to a PM, defend an architectural choice to a staff engineer, and present results to leadership without hiding behind jargon
• High ownership mentality where you treat model quality, pipeline reliability, and customer outcomes as your responsibility
• Experience building or evolving knowledge graphs, commercial ontologies, or financial data models in enterprise contexts
• Prior work on document AI, OCR pipelines, or hybrid extraction systems combining rule-based and learned approaches
• Exposure to AI agent architectures, tool-use patterns, or autonomous reasoning systems in production
• Background in procurement, contract management, spend analytics, or financial operations domains
• Experience with evaluation frameworks for AI systems (RAGAS, custom eval harnesses, human-in-the-loop QA pipelines)
• Familiarity with distributed data platforms, event-driven architectures, or streaming systems (Ray, Kafka, Azure Service Bus)
• Prior work at a high-growth startup or enterprise AI company
• An MS or PhD in a quantitative field

Benefits

• Competitive salary
• Annual performance bonus
• Employee stock option plan
• 100% paid medical, dental, and vision coverage
• 401(k) with employer contribution
• Generous vacation and sick leave
• Flexible work arrangements
• High-quality equipment for home and office
• Strong culture of collaboration, mentorship, and continuous improvement

Company Overview