Data & AI Engineer

JTA: The Data Scientists; Porto; Híbrido; EUR 45 000 - 70 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Flexible Hybrid Work System

15th Month Bonus Salary Policy

Participation in InternationalProjects

Company-Paid Certifications

Training, career progression

Resumo da oferta

JTA: The Data Scientists is looking for a Data & AI Engineer to join our hands-on team. You will develop, adapt, and run matching models and data pipelines for client projects, bridging models with scalable production results.

The role blends strong AI know‑how with solid data engineering to deliver measurable value. You will build and improve models, analyze client data, extend pipelines to new data and languages, and operate production pipelines on cloud with cost and performance awareness.

Qualificações

• Bachelor's or Master's in Data Science, Computer Science, Software Engineering, or a related field.
• 2+ years of hands‑on data science, ML engineering, or similar role.
• Solid understanding of data science concepts with real‑world data adaptation.
• Strong Python skills with pandas, Polars, scikit‑learn and software fundamentals.
• Experience with NLP or fuzzy matching and working with large datasets.
• Experience deploying data science solutions in production with APIs, cloud, and Docker.

Responsabilidades

• Develop and improve ML models and matching algorithms across data projects, from feature engineering to evaluation.
• Analyse results on client data, identify errors and patterns, and implement concrete improvements.
• Adapt models and pipelines for new data, languages, and client requirements with robust code.
• Run and monitor production data pipelines on Cloud, troubleshoot data and model issues.
• Optimize code and pipelines for performance and cost on large datasets.
• Promote best practices in code quality, model development, and lifecycle management.

Conhecimentos

Python

Data pipelines

ML engineering

NLP / fuzzy matching

Cloud platforms

Docker

Formação académica

Bachelor's or Master's in Data Science/CS/Software Eng

Ferramentas

Polars

DuckDB

Spark

pandas

scikit-learn

Descrição da oferta de emprego

We are looking for a Data & AI Engineer to join our team. This is a hands‑on role that sits at the intersection of AI and engineering. You'll develop, adapt and run the matching models and data pipelines JTA delivers to its clients, bridging the gap between the models we build and the results they produce at scale in production. You'll combine strong AI know-how with solid data engineering skills to make sure our solutions deliver tangible, measurable value.

What you will be doing:

• Develop and improve the machine learning models and matching algorithms used across our data projects, from feature engineering to evaluation.
• Analyse results on real client data, identify errors and patterns, and turn them into concrete improvements.
• Adapt and extend existing models and data pipelines to fit new data, languages and client requirements, writing robust, maintainable code across the stack.
• Run and monitor production pipelines on Cloud, troubleshooting issues across data and models and ensuring solutions perform as intended.
• Optimise code and pipelines for performance and cost on large‑scale datasets.
• Promote best practices in code quality, model development, and lifecycle management within the team.
• Contribute to internal initiatives that strengthen knowledge sharing and technical excellence across JTA's Data Science practice.

Requirements:

• Bachelor's or Master's in Data Science, Computer Science, Software Engineering, or a related field.
• 2+ years of experience in data science, machine learning engineering, or a similar hands‑on technical role.
• Solid understanding of data science and machine learning concepts, with practical experience adapting models to real‑world data and constraints.
• Strong programming skills in Python, including the data science ecosystem (e.g. pandas, Polars, scikit‑learn), with solid software engineering fundamentals (version control, testing, CI/CD).
• Experience with text processing, NLP or fuzzy matching techniques.
• Experience working with large‑scale datasets and efficient data processing frameworks (e.g. Polars, DuckDB, Spark).
• Experience deploying and operating data science solutions in production environments, including working with APIs, cloud platforms, and containerization (e.g., Docker).
• Excellent communication skills, with the ability to explain models and results to non‑technical stakeholders.
• Strong problem‑solving skills and the ability to work independently in ambiguous, fast‑moving situations.
• Flexible Hybrid Work System;
• 15th Month Bonus Salary Policy;
• Participation in International Projects;
• Company‑Paid Certifications;
• Training, career progression and support;