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Python, SQL, Pandas, NumPy, Scikit-learn, Machine Learning, Statistics
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Design, develop, analyze, and validate data-driven solutions for business intelligence and predictive analytics
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Building data pipelines and analytical models using modern data science frameworks and tools
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Development and deployment of machine learning models for classification, regression, clustering, and forecasting
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Data collection, cleaning, transformation, and feature engineering from structured and unstructured data sources
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Day-to-day collaboration with clients and stakeholders to understand business requirements and present insights and findings
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Strong experience in data validation, model evaluation, testing, and performance tuning
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Integration of data from multiple sources including APIs, databases, third-party platforms, and cloud services
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Solid foundation in statistics, probability, and machine learning concepts (e.g., hypothesis testing, regression, dimensionality reduction, model selection)