Data Scientist II (AI Deployment)

Location: São Paulo, Brazil

Company

hirify.global provides a customer engagement platform that uses messaging, journey orchestration, and AI-powered decisioning to help brands create personalized customer experiences.

What you will do

• Partner with customer Analytics/BI teams and hirify.global colleagues on use-case definition, data integration, pipeline setup, and machine learning model configuration.
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components.
• Collaborate with the reinforcement learning pipeline team to refine and advance self-learning algorithms.
• Contribute customer-facing insights and technical expertise to hirify.globalAI product strategy and roadmap.
• Provide ongoing technical guidance to support adoption, measurable outcomes, and long-term customer success.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field.
• 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or in a similar role working with large-scale data and production environments.
• Proficiency in Python, Pandas, SQL, and core machine learning libraries including TensorFlow, Keras, scikit-learn, CatBoost, and XGBoost.
• Experience with machine learning pipelines, model deployment, Git, CI/CD, testing frameworks, type hinting, code reviews, and scalable software development.
• Ability to work directly with clients and cross-functional teams and explain complex technical concepts to technical and non-technical audiences.

Nice to have

• Master’s degree or PhD in a relevant technical discipline.
• Experience in customer-facing or consulting roles.
• Experience with Airflow, Kubernetes, Terraform, GCP, data integration/ETL, pipeline optimization, or reinforcement learning algorithms.

Culture & Benefits

• Hybrid ways of working and a curated in-office experience focused on community, team connections, and innovation.
• Competitive compensation that may include equity.
• Retirement and employee stock purchase plans, flexible paid time off, and comprehensive medical, dental, vision, life, and disability benefits.
• Family services including fertility benefits and equal paid parental leave.
• Professional development through career pathing, learning platforms, and a yearly learning stipend.
• Employee Resource Groups, volunteer opportunities, donation matching, and a collaborative, transparent culture.

Hiring process

• AI-assisted tools may be used to analyze application materials, support scheduling, record interviews, and summarize interview notes.
• Recruiting teams remain responsible for hiring decisions, and candidates may have rights to request information, opt out, or request manual review depending on location.