Skilled professional who combines expertise in statistics, machine learning, programming, and domain knowledge to extract insights and build predictive models from large and complex datasets. Going beyond traditional data analysis by using advanced algorithms, statistical methods, and machine learning techniques to uncover patterns, make predictions, and solve business problems.

Should be proficient in programming languages like Python, R, and SQL, and use tools and libraries such as TensorFlow, Scikit-learn, Keras, Pandas, and Matplotlib. Their work often involves data cleaning, data wrangling, exploratory data analysis (EDA), and model development. They may build machine learning models for tasks like classification, regression, clustering, recommendation systems, and natural language processing.

A data scientist’s role also includes communicating their findings through visualizations and reports, helping businesses make informed, data-driven decisions. They are essential in fields like e-commerce, finance, healthcare, marketing, and technology, driving innovation by leveraging data to solve complex problems and optimize business processes.