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Remote senior ML role with broad Azure/PySpark requirements increases applicant competition despite seniority.
ML and big-data leadership skills are transferable but require specific Azure/PySpark experience.
Explicit 10+ years plus mandatory Azure, PySpark, ML leadership and MLOps makes filters highly strict.
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Lead and mentor a team of data scientists and analysts, ensuring technical quality and project delivery.
Design, develop, optimize, and manage ML models and big data pipelines using PySpark, Spark SQL on Azure platforms.
Architect and deploy scalable machine learning solutions with responsibility for model lifecycle management and performance tuning.
10+ years of hands-on experience in data science and machine learning development.
Proficiency in Python, PySpark, scikit-learn, XGBoost, and Spark distributed computing.
Strong experience with Azure data and machine learning services (Azure Databricks, Azure ML, ADLS, ADF).
Experience leading technical teams including code reviews, mentoring, and managing ML project execution.
Experienced leader capable of managing complex analytical problem-solving and guiding technical teams.
Skilled in integrating ML workflows within scalable cloud environments, specifically Azure.
Strong background in MLOps, CI/CD pipelines, and model operationalization with focus on performance optimization.