You will work hands-on across advanced analytics and machine learning model development, data preparation, and application development, using tools and environments including Python, GitHub, Linux, Docker, and machine learning algorithms.
Automate data extraction, cleaning, processing, feature engineering, and exploratory analysis using Python, R, and SQL across structured and unstructured operational datasets.
Develop advanced machine learning and deep learning models to support operational excellence, predict outcomes of interest, and identify patterns across enterprise datasets.
Build and deploy end-to-end analytics applications, covering data preparation, model development, and system integration.
Visualize analytical findings and model outputs using enterprise BI tools such as Tableau, Power BI, or similar platforms to create intelligent dashboards that support…
Master's degree in Data Science, AI, Statistics, Computer Science, Mathematics, or a related quantitative field.
Fresh graduates are welcome to apply.
Proficiency in Python and SQL for data manipulation, pipeline development, and model implementation.
Hands-on experience with machine learning algorithms spanning regression, classification, clustering, and deep learning methods.
Experience: Entry-level · Job type: Full-time
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