Intern Data Engineer

Barcelona - Data Engineer - Part time

800€/month
Last update: February 10, 2022

About the position

IOMED is a company specialized in the extraction and processing of medical data through Artificial Intelligence tools such as Machine Learning and Natural Language Processing. We structure clinical information with the aim of accelerating clinical research.

The scholarship is aimed at Data Science or Data Engineer students who have an interest and curiosity in new technologies and, in particular, in the Healthcare sector.

Things You Might Do 

In the Data Engineer team your main tasks will be:

  • Queries in SQL databases (specifically PostgreSQL).
  • Give support in modeling and implementation of the SQL database.
  • Realization of ETLs with SQL and Python.

Things we expect

We are looking for a person to work in the Data Engineer department, so they must be detailed, with a great capacity for concentration and analysis. In addition, we are looking for a profile that has experience using or working with SQL databases. It is an enriching experience, since projects from various areas will be tackled, in addition to working surrounded by great professionals who are eager to help the professional growth of future talent.

What we offer

  • 6 month internship contract.
  • Part time.
  • €800/month.
  • Flexible schedule.
  • Warm, transparent and supportive team, with great emphasis on reconciling work and personal life.
  • Possibility of training within the company.
  • Flexibility with remote work.
  • Most days joint meal on our sunny terrace.

About us

IOMED is a technological company of software development. It was launched in 2016, funded by local and international ventures. We are passionate and talented young professionals, from all around Spain and the world (It couldn’t be any other way, as we’re based in beautiful and bright Barcelona). Our “dream team” is made up of mathematicians, statisticians, bioinformaticians, and physicians. We are looking for people who are eager to innovate and be part of a project with an impact on the healthcare industry, enjoying what we do, team-work, and taking on new challenges. IOMED is an equal opportunity employer. We are still a small team and are committed to keep growing in an inclusive manner. We want to augment our team with talented, dynamic people irrespective of race, color, religion, national origin, sex, physical or mental disability, or age.

IOMED accelerates clinical research by exploiting clinical texts via NLP. With this purpose, we have developed our own NLP framework, which integrates a series of models to solve tasks such as Named Entity Recognition, Named Entity Linking, Relation Extraction, Word-Sense Disambiguation, Text Classification and Entity Classification. These algorithms are currently running on several hospitals in Spain, being applied to millions of clinical texts.

What we do

Nowadays, around 50% of Clinical Trials are delayed due to patient recruitment, since patient data collection is performed in a manual fashion. As a result, clinical research is highly inefficient both in time and cost, taking years and billions of dollars to develop a new drug.

This problem could be solved through Real World Data, i.e. derived from Electronic health records (EHR). But unfortunately, up to 85% of existing clinical data is unstructured, i.e. in plain text. This also leads, in part, to the existence of data silos, making it impossible to aggregate data from different hospitals.

IOMED has found the solution to this situation, making it possible to take advantage of the full value of clinical Real World Data. We developed a tool that extracts the necessary data from clinical texts, which results in a structured, standardized, and interoperable database that contains the complete clinical information from hospitals.

By this means, non-reusable information is transformed into data available for Clinical Research, allowing an enormous increase in criteria-compliant patients and a reduction of total time and manual labor devoted to this task.