Job Description
We are:
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
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.
What we offer:
- 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.
Find out more about our culture here.
