Senior Data Analyst – AI Insights & Business Strategy

Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact. With the right people and the right ideas, there's no limit to what we can achieve.

• ML/AI Translation: Interprets outputs from predictive, classification, and NLP models and converts them into executive recommendations with clear business context. Communicates technical metrics (precision, recall, AUC-ROC, SHAP values, drift) to non-technical audiences through reports and presentations.
• Advanced SQL & Python: Writes complex queries (CTEs, window functions, optimization) and Python scripts (pandas, scikit-learn, visualization) to extract, transform, and analyze data from multiple sources.
• Azure & Databricks: Experience deploying and consuming data pipelines and ML workloads in Azure cloud services and Databricks environments.
• Dashboard Development: Designs and maintains strategic dashboards in Power BI, Tableau, Looker, or similar tools to monitor business KPIs and ML model performance in production.
• Strategic Thinking: Acts as an internal consultant for business areas seeking to leverage AI/ML capabilities — evaluating feasibility, co-designing success criteria, and prioritizing initiatives by impact alongside stakeholders and technical teams.
• Data Governance & Quality: Ensures integrity, consistency, and traceability of data used in reports and dashboards; contributes to analytical and model documentation standards.
• Executive Communication & Storytelling: Comfortable presenting insights to VP and C-level audiences. Applies visual literacy principles (Gestalt, color theory) to reduce cognitive load and drive high-impact decisions.

• Model Review Participation: Experience joining data science sessions to validate the business relevance of model findings and exploratory analyses.
• AI Use Case Development: Track record identifying opportunities for new AI/ML use cases through exploratory analysis and cross-functional collaboration.
• AI Adoption Practices: Familiarity documenting and socializing AI best practices within an organization.
• Technical English: Proficiency in reading, writing, and presenting in English within technical and executive contexts.