Data Scientist

• Extract, transform, aggregate, and analyze large and complex datasets using SQL, Python, R, Spark, and related technologies.
• Perform exploratory data analysis (EDA), feature engineering, and data validation to support analytics and modeling initiatives.
• Develop, evaluate, and maintain descriptive and predictive machine learning models using tools such as scikit-learn, Jupyter Notebooks, Python, R, and/or SAS.
• Apply statistical modeling and data mining techniques, including regression, classification, clustering, decision trees, and related methodologies.
• Utilize Generative AI and AI-assisted tools, including LLMs, coding assistants, and AutoML platforms, to improve analytical workflows and insight generation.
• Apply Generative AI techniques such as prompt engineering, text summarization, classification, and LLM-assisted analysis in business or research applications.
• Collaborate with stakeholders to translate business problems into analytical solutions and communicate findings effectively.
• Build and maintain business intelligence solutions and dashboards using Tableau, Power BI, or similar visualization platforms.
• Define metrics, validate data quality, and support semantic layer development to ensure accurate reporting and business insights.
• Follow responsible AI principles, including awareness of data privacy, bias mitigation, ethical AI usage, and model limitations.

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Associate Data Scientist