Data Science Lead (Predictive Analytics & ML):

Key Responsibilities

• Lead and mentor a team of data scientists and analysts; provide technical guidance and ensure high-quality deliverables.
• Design, develop, and optimize machine learning models (classification, regression, clustering, forecasting, etc.).
• Build and maintain big data processing pipelines using PySpark, Spark SQL, and distributed computing environments.
• Architect and deploy scalable ML solutions on Azure (Azure Databricks, Azure ML, ADLS, ADF).
• Oversee feature engineering, model lifecycle management, monitoring, and performance tuning.
• Collaborate with cross-functional teams to translate business needs into analytical solutions.
• Present insights, model outputs, and recommendations to technical and business stakeholders.

Required Skills

• 10+ years of hands-on experience in data science and ML development.
• Strong hands-on experience in leading complex analytical problem solving using traditional ML architecture (like supervised and unsupervised learning, time series and Deep learning) along with strong team leadership capabilities.
• Expertise in Python, PySpark, scikit‑learn, XGBoost, and related ML libraries.
• Strong experience with Azure data and ML services.
• Solid understanding of distributed computing and performance optimization using Spark.
• Proven ability to lead technical teams, conduct code reviews, mentor juniors, and manage project execution.
• Excellent communication, stakeholder management, and problem‑solving skills.
• Experience with MLOps practices and CI/CD pipelines.