Data Science Manager manages teams tasked with identifying trends, patterns, and anomalies found in big data sets and used to develop insights by performing extensive data analysis. Oversees the interpretation of results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining. Being a Data Science Manager manages the design and implementation of big data solutions for the organization. Uses extensive knowledge and research into big data tools to guide data scientists' adoption and use of new and existing tools. Additionally, Data Science Manager typically requires a master's degree in computer science, mathematics, engineering or equivalent. Typically reports to senior management. The Data Science Manager manages subordinate staff in the day-to-day performance of their jobs. True first level manager. Ensures that project/department milestones/goals are met and adhering to approved budgets. Has full authority for personnel actions. To be a Data Science Manager typically requires 5 years experience in the related area as an individual contributor. 1 - 3 years supervisory experience may be required. Extensive knowledge of the function and department processes.
The ML Data Linguist is responsible for analyzing and processing large volumes of linguistic data to support machine learning models and natural language processing systems. They work closely with data scientists and engineers to develop and improve algorithms for language understanding and generation. The ML Data Linguist also collaborates with cross-functional teams to ensure the accuracy and quality of linguistic data used in machine learning applications. Additionally, they may be involved in creating and maintaining linguistic resources such as lexicons, corpora, and language models. Strong linguistic and computational skills are essential for this role, as well as a deep understanding of machine learning and natural language processing techniques.
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