At Digital Science we are looking for a senior software developer to join the natural language processing team based in Europe. You will be part of an experienced and highly skilled team within the exciting setting of an agile international company. Your contributions will expand and improve an existing NLP infrastructure that powers the Dimensions family of products.


  • Improve the efficiency and effectiveness of an existing NLP infrastructure that includes document classification, term extraction and research funding identification
  • Develop the insights/analytics of the quality of the NLP solutions
  • Build small, proof-of-concept/demo web applications
  • Identify areas for development

Minimum qualifications

  • At least 5 years of experience in Python development
  • Some experience or familiarity with machine learning and the information retrieval/classification measures of effectiveness
  • Familiarity with data science technologies such as Jupyter notebook, Pandas, numpy
  • Experience with relational databases
  • Experience in parallel/distributed software development
  • Experience with Docker, Kubernetes
  • Familiarity with web technologies and some experience with building proof-of-concept/demo applications e.g. Dash, StreamLit, flask
  • Exceptional problem solving and analytical skills
  • Willingness to learn new technologies

Preferred qualifications

  • An MSc or PhD in machine learning, natural language processing or related discipline
  • Experience in building machine learning models
  • Experience working with Scikit-learn, PyTorch, Tensorflow
  • Experience in processing scientific literature
  • Experience with large relational databases (e.g. Google BigQuery, Snowflake)
  • Academic-level writing skills

What We Offer

  • Be part of an international team distributed all over the globe
  • Relaxed work environment that values innovation, initiative, and energy
  • Competitive salary based on experience
  • Flexible working hours
  • Pick your own hardware

About us:

With Dimensions, Digital Science launched an innovative research data and tool infrastructure, broadening the view of the research landscape after decades of focus on the publication/citation complex. The guiding principle, to deliver context, was to take different data sets out of their silos to create a heavily interlinked overarching dataset that described the whole research lifecycle: from funding input (grants), through research outputs (publications) and translation / application of research results (clinical trials, patents), attention (altmetric and citations) and finally to policy-level impact (mentions of research results in policy papers).

In total, Dimensions today contains more than 180 million documents with more than 4 billion connections between these records. For more information please visit or try the free version of the Dimensions app at Dimensions has offices in Germany, Romania, US and UK, serving clients globally. 

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