Data Scientist

Data Scientist - Product

Location: US

Level: Senior Individual Contributor

Team: Engineering

About Terzo

Terzo builds an AI-native enterprise data platform designed to power the commercial and financial operating system of modern companies. The platform transforms complex, unstructured enterprise data into structured, actionable intelligence used directly in operational and financial decision-making. Terzo sits at the intersection of data platforms, AI systems, and enterprise software, focusing on real production use cases rather than demos or point solutions.

The Opportunity

As a Data Scientist on our Applied Research team, you will build the intelligent systems that create the data our customers depend on. You will 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, and define how AI capabilities surface as recommendations, agents, and search across the platform. You will own the models, pipelines, and graph structures that are the product — working 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.

You might thrive in this role if you have

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

You could be an especially great fit if you have

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

Why Join Terzo

Opportunity to build and own a foundational enterprise data platform

High-impact role with real influence on architecture and technical direction

Complex problems involving data, AI, scale, and enterprise customers

Small, senior team with strong ownership and minimal bureaucracy

Clear runway for technical and leadership growth as the platform scales

Benefits & Perks

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