Firjan Senai Scholarship - Call No. 0016/2026

Description

Job Summary: Develop and validate data pipelines, perform exploratory data analysis, build AI models for time series forecasting, and manage the machine learning model lifecycle. Key Highlights: 1. Opportunity to develop data analytics- and AI-based solutions. 2. Work on predictive modeling and machine learning. 3. Focus on experiment traceability and ML model management. Job Title Firjan Senai Scholarship \- Call No. 0016/2026 Professional Experience **Required Skills:** Programming for data analysis and processing, preferably in Python; **Relational database manipulation and querying (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 Skills:** Experience with data science and machine learning libraries and frameworks; **Experience with application containerization (e.g.,** Docker); Development and deployment of models via APIs; Knowledge of tools for experiment traceability and machine learning model lifecycle management; Experience integrating analytical solutions into digital systems and platforms. Academic Qualifications Bachelor’s degree in Computer Science, Computer Engineering, Data Science, Systems Engineering, Information Systems, or related fields, with academic focus on developing data analytics- 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. Perform 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 traceability 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 Contract 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. Candidate Notes **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 **Research commencement date:** April 6, 2026 Inclusion is here! Firjan encourages persons with disabilities to apply to its selection processes. Apply now!