
Cybersecurity • SaaS • BPO
Montreal Oficial is a technology company providing innovative solutions in secure identification and authentication, operational continuity, intelligent management, and automation. They specialize in advanced biometric technologies, data center and cloud solutions, and business process outsourcing. Montreal Oficial aims to support public and private institutions with efficient, secure, and connected services, driving digital transformation and addressing complex challenges faced by their clients.
1001 - 5000 employees
Founded 1986
🔒 Cybersecurity
☁️ SaaS
October 21
🗣️🇧🇷🇵🇹 Portuguese Required

Cybersecurity • SaaS • BPO
Montreal Oficial is a technology company providing innovative solutions in secure identification and authentication, operational continuity, intelligent management, and automation. They specialize in advanced biometric technologies, data center and cloud solutions, and business process outsourcing. Montreal Oficial aims to support public and private institutions with efficient, secure, and connected services, driving digital transformation and addressing complex challenges faced by their clients.
1001 - 5000 employees
Founded 1986
🔒 Cybersecurity
☁️ SaaS
• Professional from the CONTRACTOR working on modeling data repositories to support decision-making, • implementation of data extraction, transformation, and loading (ETL) processes, • design and implementation of automation and artificial intelligence applications, • processing of large-scale data, • data quality analysis, • creation and evolution of business intelligence dashboards.
• Bachelor's degree in Computer Science, Data Engineering, Data Science, or a related field; • Solid experience as a Data Scientist, focused on cloud data solutions; • Experience with programming languages commonly used in data science (Python, R, ML/AI libraries, etc.); • Knowledge of machine learning algorithms and statistical analysis; • Familiarity with data visualization tools and techniques; • Experience with SQL and database querying; • Experience with MLOps, model deployment, and monitoring; • Experience with cloud-based pipelines (preferably Azure/Databricks); • Ability to work collaboratively and manage multiple priorities; • Ability to translate complex technical concepts for non-technical stakeholders.
• Position also open to candidates with disabilities (PwD)
Apply NowOctober 21
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