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Data science, machine learning, optimization models, Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)Primary Location.
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Design, build, and maintain data pipelines from end-to-end, ensuring data accuracy, availability, and quality for the Production, Trust & Safety, and Business Analytics internal customersCollaborate closely with Data Scientists to understand data requirements, develop data models, and optimize data pipelines for advanced analytics and machine learning use cases.
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Our engineering team at OpenSea is in search of a strong, driving, but curiousData Engineer to take charge of our data replication, ETL, and warehousing infrastructure to empower our core user experiences, trust & safety models, and business intelligence use cases.
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Epocrates Engineering tech stack includes native iOS and Android apps, Java, AWS, Kafka, Knowledge Graph, SQL and non-SQL data store, React, TypeScript, Python, Vector Search DB, Docker and Kubernetes, a suite of in-house and third-party content publishing tools, A/B experiment design platform and a suite of commercial-advertising platform.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch)Primary Location.
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The Python scripts will use supervised and unsupervised ML (both text and image-based machine learning), natural language processing (named entity extraction, summarization, etc.
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Key QualificationsExperience in machine learning, deep learning, information retrieval, natural language processing or data miningExperience of prompt engineering, fine-tuning, evaluating, and developing data collection/annotation/management tooling for LLMs. Proficiency in one of following languages: Python, Go, Java, C.
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The team develops, owns and operates a suite of data science and machine learning models that feed into online systems that are responsible for personalization and search relevance.
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You will work closely with data scientists, machine learning engineers, and other software engineers, using the latest tools and technologies. - Plus for machine learning experience, especially in the area of Large Language models (LLM), Natural Language processing (NLP), and Deep Learning models.
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The Data Science and Machine Learning team work on a range of classification and optimization problems, e.g. search ranking, text/sentiment classification, and/or collaborative filtering/recommendation, to deliver the world's quality information to the people who need it.
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PhD or advanced degree in computer science, machine learning, cognitive science, psychology, economics, or similar (preferred). Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization.
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We are looking for a Senior Data Scientist to build and deploy Natural Language processing (NLP) models utilizing a variety of Machine learning and deep learning techniques.
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Strong understanding of machine learning principles, especially in the context of LLMs.5+ years of proficiency in Python, including machine learning packages like Jax/Tensorflow or PyTorch.
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Strong understanding of machine learning principles, especially in the context of LLMs. Fluent in at least one statistical programming language such as Python (preferred) or R. We are looking for an enthusiastic and technology-proficient Senior Data Scientist , who is eager to participate in design and implementation of a top-notch big data solution that will be deployed at a massive scale.
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You have experience developing solutions to machine learning & NLP problems involving some or all of the following parts of the pipeline: data extraction, developing and training machine learning models, integrating the model into production applications.
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