At GraphIQ, we've built a B2B search platform that helps users discover
information about organizations and people for partnerships, sales, and
growth. Our technology transforms public business data into a massive
knowledge graph, and we're continually expanding its capabilities.
We’re looking for an experienced, hands-on Data Scientist who brings both
creativity and pragmatism to solving tough data problems at scale. The initial
project is to develop modules for entity resolution and data cleaning in our
Python-based pipelines. From there you will take on entity linking and
information extraction, applying language models and machine learning to
expand the knowledge graph and improve how users find information.
You will be an early hire working directly with the founding team to build our
technical foundation. This is a remote role (US with work authorization or
Europe as contractor). You’ll find that at GraphIQ, we all pitch in and ask
for help when we need it, let the best ideas win, and stay focused on
delivering value to customers.
You’ll thrive here if you:
* **Have 5+ years of experience** applying machine learning and other NLP techniques to organize and connect complex, real-world data.
* **Are fluent in Python and experienced with current AI/ML techniques** : embeddings, vector databases, model fine-tuning and evaluation.
* **Design reliable data workflows** that standardize, canonicalize, and link structured and unstructured data across diverse sources.
* **Understand how knowledge connects**. You’ve built or worked with knowledge graphs, entity linking, or semantic search, and you enjoy modeling data to make it more discoverable.
* **Take ownership of problems and projects**. You’re comfortable defining scope, making design choices, and writing well-structured code that integrates into production pipelines.
* **Work collaboratively and pragmatically**. You contribute ideas, listen to feedback, ask for help when you need it, and focus on customer impact.
* **Balance experimentation with practical execution**. You can prototype quickly, build what works, and ship code that solves real problems.
* **Stay engaged with emerging AI capabilities** like agentic workflows and tool-calling systems, and know how to evaluate what's worth adopting for our specific needs.
If you love making data make sense, and want your expertise to make a direct
impact, we’d love to hear from you.