Data Scientist - AI and NLP

At Uni Systems, we are working towards turning digital visions into reality. We are continuously growing and we are looking for a professional Machine Learning Engineer to join our UniQue Ispra team.

In this role, you will have the opportunity to work closely with our customers in the public sector and you will be responsible for developing new business by identifying profitable opportunities, maintaining your client portfolio by building strong, long-lasting relationships, and monitoring the progress of the projects, with the aim to provide excellent client service and added value services.

What will you be bringing to the team?

• Collect business requirement and develop advanced data mining solutions or identify, assess and deploy relevant existing data mining, machine learning and business intelligence solutions, in detail:
• To analyse user needs and requirements
• To identify and propose alternative implementations to support user requirements
• To architect a final system solution
• To contribute to the implementation of the identified architecture.
• To devise quality, security and architectural plans and assist in their implementation
• Develop specifications and design of presentation interfaces with optimal usability/user experience; follow up with their implementation;
• Identify, collect, convert and update different data types/sets in several locations;
• Produces data models according to specific problems statements;
• Scripting and programming;
• Contribute to the design and implementation of the analytics architecture and its solution stack (including performance aspects, physical design, capacity dimensions etc…)
• Write the different documentation associated with the tasks and liaise with other project teams as necessary to address cross-project interdependencies.

Requirements

• Master Degree + 3 years of relevant professional experience
• At least 3 years of experience in statistical computing and data visualization using R, SAS, SPSS, STATA or equivalent platforms.
• At least 2 years of experience in:
• Scripting and programming using Python and JavaScript.
• Database architecture and query development, covering SQL and NoSQL technologies such as MySQL, PostgreSQL, Microsoft SQL Server, MongoDB and Elasticsearch.
• At least 1 year of experience in:
• Using Python to collect, clean, process and analyze structured and unstructured data, with libraries such as pandas and NumPy or equivalent tools.
• Applying machine learning and natural language processing (NLP) to textual data for information extraction, document classification, clustering and semantic similarity, using tools such as spaCy, scikit-learn and Sentence Transformers or equivalent technologies.
• Using large language models (LLMs) for structured information extraction, classification and summarization, including prompt development and verification of outputs against source evidence.
• Assessing data quality and validating analytical outputs, including comparison with human-reviewed examples, error analysis, and documentation of uncertainty and limitations.
• Identifying trends and patterns, synthesizing information from multiple sources, and preparing analytical summaries, reports or briefs in English, with accurate referencing and clear presentation of findings.
• Excellent knowledge of data analytics techniques and their mathematical foundations; basic knowledge of multivariate analysis and principal component analysis is desirable.
• Strong background in machine learning and NLP.
• Desirable expertise in one or more of the following: predictive modelling, forecasting, prescriptive analytics, simulation, sentiment analysis, topic detection, social media analytics, trend and anomaly detection, and recommendation systems.
• Proficiency in business intelligence, data visualization and ETL tools, such as SAP, BusinessObjects, Tableau and Talend Open Studio.
• Knowledge of web application architectures, including HTML5, CSS3, APIs and backend technologies such as .NET/C#, Node.js/Express.js and Spring Boot/Java.
• Experience with Unix environments and DevOps practices, including continuous integration and delivery, automated testing, containerization and orchestration, using tools such as GitLab and OpenShift.
• Good oral and written communication skills in English.