S

Source

Global data ecosystem linking intelligence providers

Data Scientist

Applied Machine LearningUpdated on Nov 7
Full-timeVilnius, Vilnius City Municipality, Lithuania€4k - €6.5k /moHybrid

About the Job

Requirements

  • At least 4 years of experience as a Data Scientist, Data Analyst, or Data Engineer, with a strong background in data modeling, machine learning, and natural language processing.
  • Strong programming skills in Python, proficiency in SQL, and hands-on experience with Spark.

Responsibilities

  • Develop and maintain entity-resolution techniques to match and link records across sources with inconsistent identifiers.
  • Prototype, build, and evaluate large language model and machine-learning-based extraction and inference models that turn unstructured or free-text data into structured outputs.
  • Automate scraping logic and source queue generation using data-driven models to streamline and scale source acquisition workflows.
  • Build, iterate on, and monitor applied machine-learning models to proactively identify data or concept drift.
  • Enrich and enhance datasets with product-ready calculated fields and derived metrics.
  • Assist in building automated or ad-hoc quality-assurance validation processes to validate model-output accuracy, reliability, and consistency.

Desired Qualifications

  • Experience with Dagster, dbt, Superset, or Trino.
  • Previous experience working closely in a team with data engineers.
  • Strong business acumen and an understanding of how insights convert to value and unlock new revenue.
  • Excellent written and spoken English.

About the Company

Source

Global data ecosystem linking intelligence providers

The company operates as a data ecosystem that connects several independent tech firms—Oxylabs, Decodo, Webshare, ScrapingBee, Honeygain, and upcoming ventures—under shared standards, strategic support, and a commitment to responsible access to data. Each member company runs its own team and product, but they collaborate through common intelligence and scale to serve a wider market. Their approach is to provide a networked set of data tools and services that collectively enable customers to access and use data more efficiently. The goal is to empower the next generation of data-powered products and decisions by offering interoperable capabilities and scalable data access while maintaining clear accountability for data use.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Boston, MA
Founded
2012

Recently Posted Jobs

Explore more opportunities at Source

See more jobs