Tareas
- Design statistical, machine learning, and generative AI solutions for high-value use cases such as forecasting, classification, anomaly detection, recommendations, optimization, and text analytics.
- Use Microsoft Fabric to explore data, engineer features, train models, and track experiments with MLflow.
- Design experiments and evaluations, interpret results rigorously, and translate findings into trusted recommendations and measurable improvements.
- Support generative and agentic AI use cases by evaluating model behavior, improving prompts and grounding, and identifying where models, insights, or agents create value.
- Use Microsoft Foundry to prototype, test, optimize, and evaluate AI applications and agents using enterprise data, models, and tools.
- Ensure models and analytical products meet governance, privacy, lineage, and responsible AI requirements in collaboration with Purview and governance stakeholders.
- Contribute reusable assets such as feature logic, evaluation methods, notebooks, experimentation patterns, and documentation standards.
Perfil
- Minimum 5 to 7+ years of professional experience in data science, ML, applied machine learning, advanced analytics in enterprise or product settings, econometrics, statistics, operations research, or a closely related field.
- Proven track record of delivering production-relevant analytical or ML solutions that drive measurable business outcomes.
- Experience working with cross-functional teams including data engineering, architecture, product, and business stakeholders.
- Experience in regulated, enterprise-scale, or governance-heavy environments is highly desirable.
- Solid grounding in statistics, experimentation, predictive modeling, and model evaluation to select fit-for-purpose methods.
- Practical Microsoft Fabric experience with notebooks, experiments, analytics assets, and collaboration with data and analytics teams.
- Familiarity with ML flow, experiment tracking, and reproducible analytics workflows.
- Good understanding of Azure-native AI patterns, including evaluation, observability, grounding, and lifecycle management in Microsoft Foundry.
- Ability to embed data science outputs into AI applications, copilots, or agents in collaboration with Copilot Studio or similar teams.
- Awareness of governance, information protection, and responsible AI controls for predictive and generative AI use of enterprise data.
- Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
- Microsoft Certified: Fabric Data Engineer Associate (DP-700)
Contacto
tkMits-IN-Recruitment@thyssenkrupp-materials.com
