Big Data, IoT and analytics (BIA)- Internship Business Studies and/or Management Science, Communication and Information Sciences, Mathematics and/or Informatics
This is a Digital Opportunities Traineeship (DOT). If you want to apply for this internship, please remember that you have to be a student or recently graduated based in one of the 33 Programme Countries participating in Erasmus+ or the Horizon 2020 Associated Countries.
Before applying for a Digital Opportunity Traineeship we encourage you to check with your university if you are eligible for Erasmus+ traineeship. You can read more about DOT's in our information page.
General information
Duration: 6 months
Commitment: Part-Time
Description: Are you a tech‑savvy individual with a passion for data, IoT, and analytics? If you're eager to dive into the world of big data and IoT while gaining hands‑on experience with diverse data science methodologies and technologies, we invite you to join our Data Unit at Proceedit. We're seeking ambitious interns who are ready to explore, analyse, and unlock the potential of data.
About Us:
Proceedit is a software development company specialising in business process automation. We simplify your work by transforming your business, managing its complexity, and facilitating collaboration with your different stakeholders. As a result, by applying our BPaaS business model, we agile your operations, control your processes, and maximise your margins without requiring any investment. We're dedicated to pushing the boundaries of what data can do, providing valuable insights to our clients and partners.
As a Big Data, IoT, and Analytics Intern at Proceedit, you'll be an integral part of our Data Unit, working on a wide range of data‑related projects, including open and big data, structures and ontologies, statistics and analytics, search and semantics, and database management. Your responsibilities will include:
* Open and Big Data: Contribute to the collection and analysis of open and big data sources.
* Structures and Ontologies: Assist in structuring data and defining ontologies to extract meaningful insights.
* Statistics and Analytics: Collaborate with our data scientists to perform statistical analysis and derive actionable insights.
* Search and Semantics: Work on projects involving data search, semantic analysis, and building intelligent search systems.
* Databases Management: Help manage and optimise databases to ensure data is accessible and secure.
Qualifications:
* Pursuing or recently completed a degree in Data Science, Computer Science, or a related field.
* Understanding of relational databases and experience in writing SQL queries for data.
* Basic programming skills in Python (Knowledge of NumPy and Pandas libraries is recommended).
* Knowledge of Data Structures, algorithms, time and space complexity.
* Experience with data pipelines and ETL methodologies.
* Ability to extract data from websites using web scraping techniques and tools.
* Proficiency in data visualisation tools and libraries to create insightful visual representations of data.
* Strong analytical and problem‑solving skills.
* Curiosity and a willingness to learn and adapt to new data science methodologies and technologies.
* Excellent communication and teamwork abilities.
We are looking for candidates who can join immediately.
What We Offer:
* A dynamic and collaborative work environment.
* Mentorship from experienced data scientists and data engineers.
* Hands‑on experience with diverse data science projects.
* The opportunity to work on projects that have a real‑world impact.
* Compatible with participation as part of the Erasmus or a similar internship exchange programme.
* Possibility to develop the final course degree project for your academic institution as part of the internship period.
* Compatible with the realisation of your Master or PhD thesis.
* Academic Certificate and Professional Working Certificate.
* Recommendation Letter and LinkedIn Professional Recommendation.
* Financial compensation by participating on the trainee pathway (but only in the second phase of the internship).
Keywords
Spain Data base Management Analysis statistics
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