Firjan Senai Scholarship - Call No. 0016/2026

Description

Job Summary: Develop and optimize data pipelines and Artificial Intelligence models for predictive analysis of time series and regression, integrating analytical solutions into digital platforms. Key Highlights: 1. Optimization of AI and Machine Learning models for data analysis. 2. Development of data pipelines and ETL/ELT processes. 3. Feature engineering and exploratory data analysis. Job Title Firjan Senai Scholarship \- Call No. 0016/2026 Professional Experience **Knowledge Requirements:** Programming for data analysis and processing, preferably in Python; **Manipulation and querying of relational databases (e.g.,** SQL Server, PostgreSQL, or similar); Development of data pipelines and ETL/ELT processes; Exploratory data analysis and feature engineering; Application of machine learning techniques and predictive modeling; Time series modeling and analysis. **Desirable Knowledge:** Experience with data science and machine learning libraries and frameworks; **Experience with application containerization (e.g.,** Docker); Development and deployment of models via APIs; Familiarity with tools for experiment tracking and machine learning model lifecycle management; Experience integrating analytical solutions into systems and digital platforms. Academic Qualifications Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Systems Engineering, Information Systems, or related fields, with a focus on developing data-driven and Artificial Intelligence-based solutions. Job Responsibilities Develop and validate data ingestion, processing, and pre\-processing pipelines (ETL/ELT), including extraction, integration, and anonymization of data from various relational databases. Conduct exploratory data analysis and feature engineering, creating derived variables and analytical indicators representing temporal behaviors, demand patterns, seasonality, and other factors relevant to predictive modeling. Develop, train, test, and optimize Artificial Intelligence models for time series forecasting and regression problems, using machine learning techniques and algorithms applied to operational data analysis. Package and deploy developed models via containers and Application Programming Interfaces (APIs), enabling integration with computer systems and digital platforms. Implement mechanisms for experiment tracking and machine learning model lifecycle management, ensuring documentation of experiments, reproducibility of results, and organization of data used during technological research and validation. Number of Positions 1 Work Location Remote Salary Range R$1\.500,00 to R$2\.000,00 Employment Type Fixed-term contract Recruitment Process Details Curriculum Screening\* Technical Interview\*\* Document Submission\*\*\* The candidate’s approval will be determined based on information provided in the resume and performance in the technical interview conducted by the managing unit. * Not scored. \*\* Scored; qualifying stage. \*\* Not scored; elimination stage. Notes (for Candidates) **Resume submission period:** March 12, 2026 to March 22, 2026 **Screening period:** March 23, 2026 to March 24, 2026 **Interviews:** March 25, 2026 to March 26, 2026 **Results announcement:** March 27, 2026 **Document submission deadline:** March 30, 2026 **Start date of research work:** April 6, 2026 Inclusion is here! Firjan encourages participation of people with disabilities in its selection processes. Apply now!