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9,099 jobs found
09.09.2025
JPM
JPMorgan Machine Learning Scientist - NLP Senior United States, New York, New York
Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community. Develop state-of-the art machine learning models to solve real-world...
Lead and manage a team of Client Service Professionals, fostering a culture of continuous improvement and innovation to enhance the efficiency and resilience of our operating platform. Develop and implement...
Communicate and interface with senior stakeholders, leveraging analytical skills and business acumen to drive impactful results that inform strategic decisions. Commit to iterative development, engaging and updating stakeholders bi-weekly or...
Work on designing new data models for domains such as financials and forecasting models across different scenarios and work on some of the most complex and highly visible data problems...
Serve as a subject matter expert on a wide range of ML techniques and optimizations. Build and enhance ML workflows through advanced proficiency in large language models (LLMs) and related...
Responsible for all aspects of data strategy, governance, data risk management, reporting and analytics. Work with product owners, data owners and customers to evaluate data requirements and identify right technology...
Engage with stakeholders to understand & document business requirements. Understand business problems and opportunities in the context of the requirements and recommend solutions that enable the organization to achieve business...
Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community. Develop state-of-the art machine learning models to solve real-world...
Data Scientists are responsible for analyzing and interpreting large and complex datasets to uncover insights that inform business decisions and drive innovation. They use a combination of statistical and machine learning techniques, as well as programming languages such as Python and R, to extract, clean, and transform data. They also use tools such as SQL, Hadoop and Spark to work with large datasets and perform data analysis.
Data Scientists work closely with cross-functional teams, such as product managers, marketing and operations, to understand their specific data needs and provide them with insights to make informed decisions. They also collaborate with data engineers to build and maintain the infrastructure necessary for data analysis. They also use data visualization tools such as Tableau and Power BI to create interactive dashboards and reports to communicate data insights clearly and effectively to non-technical stakeholders.