Data Scientist – AI
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Key skills for this role
About the Role
Miral Destinations seeks a Data Scientist to join its AI team, analyzing data and developing AI/ML models to support business objectives. You will build RAG pipelines, vector databases, and LLM solutions on Databricks, and collaborate with ML Ops to deploy models.
Key Skills for This Role
Responsibilities
- Analyze Miral Destination datasets to uncover patterns, trends, and opportunities
- Develop, train, and fine tune AI and machine learning models tailored to Miral Destination use cases
- Build RAG pipelines, vector databases, and LLM based solutions on Databricks
- Generate clear, actionable insights and visualizations that support business objectives
- Collaborate with ML Ops Engineer to operationalize models and ensure production readiness
- Translate stakeholder requirements into data science deliverables
Requirements
- 3 5 years in Data Science, Machine Learning, or Advanced Analytics
- Demonstrated experience taking models from analysis through to deployment
- Strong data analysis, statistical modeling, and machine learning skills
- Hands on experience with Python and Databricks (incl. MLflow)
- Understanding of RAG, LLMs, and vector databases
- Bachelor's or Master's in Data Science, AI, Statistics, Computer Science, or related field
Full Job Posting
Job Overview
- Serve as a dedicated Data Scientist within the Miral Destination AI team, developing AI/ML models and generating insights.
Job Scope
- Analyze Miral Destination datasets to uncover patterns and trends.
- Develop, train, and fine tune AI/ML models.
- Build RAG pipelines, vector databases, and LLM solutions on Databricks.
- Generate actionable insights and visualizations.
- Collaborate with ML Ops to operationalize models.
- Translate stakeholder requirements into data science deliverables.
- Align work with enterprise AI architecture and governance.
Job Essentials
- 3 5 years in Data Science, Machine Learning, or Advanced Analytics.
- Experience taking models from analysis to deployment.
- Strong data analysis, statistical modeling, and ML skills.
- Hands on experience with Python and Databricks (incl. MLflow).
- Understanding of RAG, LLMs, and vector databases.
- Data storytelling skills.
- Collaboration with ML Ops.
Education
- Bachelor's or Master's in Data Science, AI, Statistics, Computer Science, or related field.
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