Lead Data Scientist
Starlink Qatar
Posted today
Job DescriptionPermanent
We are seeking an experienced Lead Data Scientist to spearhead the development and deployment of data-driven solutions on our innovative digital platform in Doha, Qatar. In this pivotal role, you will apply advanced analytics, machine learning, and statistical modeling to derive actionable insights from complex datasets, directly influencing business strategy and enabling intelligent services. You will guide a team of data scientists, fostering a culture of innovation and continuous improvement.
This position requires close collaboration with data engineering, architecture, and operations teams to operationalize models through robust MLOps practices. Your expertise will be crucial in managing the entire model lifecycle, from data preparation and model development to deployment, monitoring, and optimization, ensuring our solutions deliver sustained, measurable value.
- 10+ years of professional experience in Data Science and Machine Learning roles.
- Proven track record of leading and mentoring data science teams.
- Advanced proficiency in Python and its data science libraries (e.g., scikit-learn, Tensor Flow, PyTorch, pandas).
- Hands‑on experience implementing CI/CD pipelines and MLOps using tools like MLflow, Databricks, and Microsoft Fabric.
- Deep understanding of the complete machine learning model lifecycle, including monitoring, A/B testing, and performance tracking.
- Expertise in statistical modeling, predictive analytics, and experimental design.
- Significant experience building large‑scale analytical solutions with cloud platforms, specifically Azure Synapse Analytics, Azure Stream Analytics, and Azure HDInsight.
- Strong background in the IoT domain, with exposure to smart city or infrastructure analytics.
- Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative discipline.
- Demonstrated ability to translate complex analytical concepts into actionable business insights for non‑technical stakeholders.
- Experience working closely with Data Governance and Architecture teams to ensure model compliance and integration.
- Creative problem‑solving skills with a history of developing innovative analytical methodologies.
- Strong business acumen with the ability to align data science initiatives with strategic KPIs.
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