Visual Analytics & Data Science Analyst

Description

Job Summary: Support the development and maintenance of data routines and analytical solutions, contributing to information quality and reliability, as well as business decision-making. Key Highlights: 1. Positions available for Junior and Mid-level professionals 2. Focus on data analysis and visualization 3. Collaborative work with the technical team Support the development, maintenance, and execution of data routines and analytical solutions, contributing to information quality, organization, and reliability, as well as to building analyses and visualizations that support business decision-making, under guidance from the technical team and management. **Open position for Junior and Mid-level professionals** Candidates will be evaluated based on their performance at each stage of the process. **Academic Qualifications\- Junior and Mid-level** Currently pursuing a bachelor's degree in Data Science, Information Technology, Information Systems, Systems Analysis, or related fields. **Mandatory Technical Skills\- Junior** Tools: Familiarity with SAS Visual Analytics is desirable; Proficiency in Power BI; Languages: Knowledge of Python or R. Statistics: Understanding of Machine Learning, regression analysis, decision trees, and time series. Visualization: Principles of UX Design and visual standardization. Dashboard development. Data: Proficiency in SQL. Knowledge of ETL. **Mandatory Technical Skills\- Mid-level** * Basic knowledge of data engineering and processing; * SAS language (DATA STEP and PROC SQL); * Concepts of data modeling and SQL; * Visual Analytics and dashboard development; * Basic understanding of data quality and organization. **Desirable Courses and/or Certifications \- Mid-level** * Courses in SAS, BI, Analytics, or related areas; * SAS certifications. **Technical Competencies \- Junior** Tools: Familiarity with SAS Visual Analytics is desirable; Proficiency in Power BI; Languages: Knowledge of Python or R. Statistics: Understanding of Machine Learning, regression analysis, decision trees, and time series. Visualization: Principles of UX Design and visual standardization. Dashboard development. Data: Proficiency in SQL. Knowledge of ETL. **Technical Competencies \- Mid-level** * SAS DATA STEP and PROC SQL; * SAS Visual Analytics (basic dashboard development); * SAS Studio and Enterprise Guide; * Data treatment, validation, and analysis; * Basic technical documentation; * Basic understanding of data governance and quality; * Initial familiarity with version control (Git or similar) **Main Responsibilities \- Junior** * Analytical Development: Create dashboards in SAS VA with a focus on storytelling, ensuring both technical clarity and visual aesthetics. * Exploratory Data Analysis (EDA): Identify patterns, trends, and anomalies in data prior to final visualization. * Technical Liaison: Translate complex statistical metrics into understandable indicators for managers and business units. * Validation and Documentation: Support validation and review activities with business units. Document objects, layouts, and published versions. **Main Responsibilities \- Mid-level** * Support data lifecycle activities, including data preparation, integration, and organization; * Develop and maintain data processing routines using SAS language, under technical supervision; * Code SAS routines (DATA STEP, PROC SQL, and basic macros) for data manipulation, transformation, and consolidation; * Assist in automating data loads and executing scheduled processes; * Perform data treatment, integration, and validation, following defined guidelines and standards; * Support dataset modeling for use in analyses, reports, and dashboards; * Develop reports, analyses, and dashboards in SAS Visual Analytics, focusing on operational and analytical KPIs; * Assist in verifying data quality and consistency by applying basic validations and controls; * Support validation processes, identifying and reporting inconsistencies; * Contribute to improving query and routine performance, under guidance; * Follow project-established security, governance, and data best practices; * Collaborate with the technical team and user departments to support understanding of business requirements; * Document developed routines, processes, and analyses to ensure traceability and ease of maintenance.