Project & AI Analyst II

Azzas 2154 | Fashion & Lifestyle Men

. Lead end-to-end AI projects within the Wholesale business.

Posted 10/22/2026full-timeRio de Janeiro • BrazilMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in leading AI projects within the Wholesale business, translating complex business problems into effective technical solutions while ensuring clear communication and collaboration with stakeholders. Exhibits strong technical execution skills in AI tools, data management, and automation, fostering a culture of knowledge sharing and collective growth.

Highest-signal resume keywords

AI Solutions ImplementationData ManagementTechnical Execution SkillsStakeholder EngagementCritical Thinking

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

AI ToolsAutomationAnalyticsModelsAPIsVisualizations

Soft Skills

Clear CommunicationCollaborative MindsetAutonomyInformal Influence

Industry Keywords

Wholesale BusinessTechnical LeadershipBusiness ContextsValue and Quality Focus

About the role

Key responsibilities & impact

Lead end-to-end AI projects within the Wholesale business.
Translate business problems into appropriate technical solutions, including automation, analytics, models, agents, and applications.
Select, implement, and integrate AI solutions with a focus on value, speed, and quality.
Engage directly with senior stakeholders, influencing decisions and priorities.
Serve as a technical and practical reference for other analysts.
Share learnings and solutions with the team, fostering collective growth.
Engage the Tech Lead when identifying stack limitations or significant architectural challenges.

Requirements

What you’ll need

Strong technical execution skills, using code, platforms, and AI tools in an integrated manner.
Experience with AI solutions applied to real-world business contexts.
Ability to work with data, models, APIs, automations, and visualizations.
Critical thinking to evaluate technical trade-offs and business impacts.
Comfort working in environments that are still maturing.
Clear communication with business teams.
Autonomy and a strong sense of ownership.
Ability to challenge requests and redirect efforts toward areas with the greatest value.
Informal influence and a technical leadership mindset.
Collaborative mindset and willingness to share knowledge.