Data Science

• Identify the target audience using filters in HR systems, taking into account employment relationship, work arrangement, organizational area, and assignment or secondment status
• Extract work hours, absence, attendance, substitution, and timekeeping records for the defined reference periods
• Cross-reference system configuration data to build an identification key for each employee’s work schedule plan
• Project work schedules day by day based on shift-cycle logic
• Apply data-cleansing and exclusion rules to ensure the eligibility of the records analyzed
• Compare expected entries with those registered in the system, identifying required additions, updates, and blocks
• Engage the IT team to execute bulk entries
• Consolidate timekeeping records into clock-in and clock-out pairs for time-based analysis
• Identify anomalous patterns in special work arrangements, including recurring daytime schedules and weekends off

• Bachelor’s degree in a technology-related field
• Python: data manipulation, automation, and development of analytical solutions
• SQL: data extraction and transformation from relational databases
• Statistical modeling and machine learning techniques applied to data analysis
• Machine learning and visualization libraries: Scikit-learn, Streamlit, Matplotlib/Pyplot
• Deep learning frameworks: TensorFlow and PyTorch
• NLP, Generative AI, LLMs, and RAG (Retrieval-Augmented Generation)
• Cloud computing: AWS and Azure
• Experience with LangChain and LangGraph
• Experience building chatbots
• Communication and collaboration with technical teams
• Ability to act as an interface between business and IT
• Presentation of results to non-technical audiences

• Remote work
• Position also open to candidates with disabilities