Chemical Data Scientist

Valdera

$120K — $150K *
Pharmaceuticals & Biotech
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in data science, data engineering, or applied data roles involving messy datasets.
  • Working knowledge of chemistry, understanding CAS numbers, and chemical properties.
  • Strong Python skills for building web scrapers and data pipelines.
  • Experience in data cleaning and normalization at scale.
  • Familiarity with matching and classification model development.
  • Hands-on experience with AI tools and LLMs for data workflows.
  • Startup mindset emphasizing ownership and adaptability in a fast-moving environment.

Responsibilities

  • Design and build data collection pipelines for supplier and chemical product information.
  • Develop and maintain web scrapers and automated ETL workflows for current data management.
  • Clean, normalize, and reconcile inconsistent supplier data into structured formats.
  • Validate and enrich data using chemical domain knowledge to resolve inconsistencies.
  • Improve models for matching suppliers and products to buyer requirements.
  • Collaborate with Supplier Management and Engineering to establish data quality standards.
  • Drive pipeline health and data quality metrics.

Benefits

  • Generous employee benefits package with detailed options provided before joining.
Full Job Description
Role Description:

We are hiring a Chemical Data Scientist to build and maintain the pipelines that keep Valdera's supplier and chemical product data accurate, current, and structured - the foundation every buyer and supplier relies on across Valdera's procurement platform.

Data quality plays a critical role at Valdera. When a buyer launches a request, they expect to be matched with the right suppliers and accurate specs on the first try. Delivering that depends on clean, current data - CAS numbers, specifications, certifications, and regulatory documents pulled from thousands of inconsistent, often messy sources. This requires strong data engineering fundamentals and a working knowledge of chemical industry data. For example, you might take dozens of differently structured chemical supplier catalogs and turn them into one clean, standardized product database.

You will take ownership of the full data pipeline - from scrapers and ETL workflows to data cleaning, matching, and classification models that connect suppliers to buyer requirements. You're energized by messy, real-world data and confident partnering with Supplier Management and Engineering to close coverage gaps. As a data-obsessed professional, you're dedicated to the accuracy our buyers and suppliers depend on.

Role Responsibilities:

  • Design and build pipelines to collect supplier data and chemical product information (specifications, CAS numbers, certifications, SDS/regulatory documents, NAICS classification of manufacturing plants) from supplier sites, distributor catalogs, trade databases, and other public and semi-structured sources
  • Develop and maintain web scrapers and automated ETL workflows to keep supplier and product data current at scale
  • Clean, normalize, and reconcile inconsistent supplier data into structured, standardized formats suitable for internal tools and analytics
  • Apply chemical domain knowledge to validate and enrich data - resolving product names, CAS numbers, synonyms, and specifications across suppliers
  • Evaluate and improve matching and classification models to map suppliers and products to buyer requirements, and to identify overlapping or equivalent chemical offerings
  • Partner with Supplier Management and Engineering to define data quality standards, identify gaps in supplier coverage, and prioritize new data sources.
  • Own pipeline health and data quality, and drive the KPIs that measure overall data coverage


Experience & Qualifications:

  • 5+ years of experience in a data science, data engineering, or applied data role, ideally with exposure to messy, real-world or industrial datasets.
  • Working knowledge of chemistry or chemical industry data - comfort with CAS numbers, chemical properties, SDS documents, NAICS classification, and supplier certifications
  • Strong Python skills, with experience building web scrapers and data pipelines
  • Experience with data cleaning and normalization at scale, and a good eye for spotting inconsistencies in unstructured data
  • Familiarity with building or applying matching, deduplication, or classification models (traditional ML or LLM-based approaches)
  • Hands-on experience using AI tools and LLMs to accelerate data extraction, enrichment, or engineering workflows
  • Startup mindset with a strong sense of ownership - comfortable working independently in a fast-moving, remote environment with ambiguous, evolving priorities


Salary Range:

Salary ranges are determined by multiple factors, including the labor market, market compensation bands, internal parity, and budget considerations. The final offer will be based on the candidate's individual skills, qualifications, location, and experience relative to the requirements of the role.

Benefits:

Valdera offers generous benefits to employees. You will be provided a more detailed breakdown of your options prior to joining Valdera.

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