[Hiring] Senior Data Scientist – AI Strategy & Advanced Analytics @WIZELINE

Role Description

We are Wizeline, a global AI-native technology solutions provider, developing 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.

Are you a fit? Sounds awesome, right? Now, let’s make sure you’re a good fit for the role:

• Must-have Skills:
• Advanced Modeling: Leads end-to-end design of high-complexity models, including deep learning, advanced forecasting, optimization, and NLP.
• Data Science Strategy: Partners with senior leadership to define data science strategy and roadmaps, guiding the analytical direction of the organization.
• Feature Engineering & Experimentation: Architects feature engineering frameworks, experimentation standards, and modeling conventions. Applies strong knowledge of experimentation and causal inference.
• Azure & Databricks: Oversees deployment and integration of models using Spark and Databricks. Strong experience deploying models in Azure Databricks using MLflow.
• Model Monitoring: Skilled in monitoring model performance and detecting model drift in production environments.
• Technical Leadership: Mentors and technically guides L1 and L2 Data Scientists. Reviews and standardizes best practices for code, modeling, documentation, and validation.
• ML + BI Integration: Applies strong critical thinking to integrate machine learning outputs with business intelligence tools (Power BI preferred) to drive business impact.
• Executive Communication: Communicates analytical direction and insights to C-level and VP-level stakeholders.
• Technical English: Proficiency in reading, writing, and presenting in English within technical and executive contexts.
• Nice-to-have:
• AI Genie (Databricks): Experience working with AI Genie in Databricks environments.
• Thought Leadership: Publications, open-source contributions, training, or conference participation.
• Data & AI Governance: Exposure to data and AI governance and enterprise data strategy.
• AI Tooling Proficiency: Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows.
• Leadership experience in ML platform or DevOps teams.
• Experience with feature stores and feature engineering. AutoML is a plus, H2O is a plus.

Benefits

• A High-Impact Environment
• Commitment to Professional Development
• Flexible and Collaborative Culture
• Global Opportunities
• Vibrant Community
• Total Rewards
• *Specific benefits are determined by the employment type and location.