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1,977 jobs found
17.03.2024
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PayPal Data Scientist United States, California, San Jose
:Master’s degree, or foreign equivalent, in master’s degree, or foreign equivalent, in Computer Science, Information Systems, or closely related field plus one year of experience in the job offered as...
Required Qualification:Bachelor's degree or equivalent degree in Statistics, Mathematics, Computer Science, or Computer Engineering and six (6) months of experience in the job offered or closely related data engineering role.Must...
Explore high-level, undefined ideas and business problems using structured and unstructured data. Develop product offerings through careful consideration of business value and data analysis. Build and fine-tune deep learning and...
Research and develop new methodologies for demand forecasting. Improve upon existing methodologies and implement model enhancements. Drive scalable solutions. Create and track accuracy and performance metrics (both technical and business...
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related fieldo OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or...
Collaborative Ideation: Work closely with engineering and product to brainstorm, design, and validate new features and improvements based on data-driven insights. Resource Optimization: Partner with SREs to optimize resource usage,...
Support the lead in providing oversight of high-impact statistical models and AI applications in various business functional areas, focusing on but not limited to Natural Language Processing (NLP) models and...
:Master’s degree, or foreign equivalent, in master’s degree, or foreign equivalent, in Computer Science, Information Systems, or closely related field plus one year of experience in the job offered as...
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.