Chemical Data Scientist - Material Informatics

ChampionX•Sugar Land, TX

2d•Onsite

About The Position

We are looking for a highly motivated Chemical Data Scientist in our Chemical Artificial Intelligence group located in Sugar Land, Texas. The Chemical Data Scientist will focus on material informatics and sourcing databases. If you are a passionate professional that likes to work in an autonomous, hands-on environment, we invite you to apply. This is your opportunity to join a growing company offering a competitive base salary and benefits.

Requirements

Ph.D. in Chemistry, Geology, Chemical Engineering, Data Engineering, Petroleum Engineering or related fields with 6+ years of experience; or M.S. in Chemistry, Geology, Chemical Engineering, Petroleum Engineering, or related fields with 8+ years of experience
Prior experience with material informatics and sourcing databases
Strong data curation + data engineering skills (Python, SQL) and QA automation.
Experience standardizing messy multi-source technical datasets (taxonomy, metadata, entity resolution).
Feature engineering and alignment across heterogeneous sources; similarity search/cheminformatics is a plus.
Ability to work across R&D and sourcing/procurement stakeholders.

Nice To Haves

Specialty chemicals/materials domain familiarity (surfactants, inhibitors, polymers, solvents, etc.).
Experience at a major specialty-chemicals vendor or in supply chain/procurement (vendor management, sourcing strategy, supplier qualification, lead-time/cost drivers).
Synthetic chemistry/manufacturing awareness to add feasibility/scale-up and rough cost/manufacturability signals.

Responsibilities

Collect vendor/material data (structures, composition, specs, properties, SDS/TDS where available) and maintain data quality/governance.
Design canonical schema and mapping logic; implement feature alignment, unit normalization, synonym/entity resolution, and version control.
Build analytics-ready datasets for AI/ML or simulation workflows (features, embeddings, metadata, similarity/search).
Establish “candidate-to-action” roadmap: supplier options, substitutes, risk flags, and early cost/lead-time signals for buy vs. synthesize decisions.
Collaborate with technical team and procurement to validate recommendations and continuously improve database coverage and accuracy.