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The ideal candidate has both a theoretical and practical understanding of deep learning techniques and has a proven track record in areas such as clinical research, computational biology, probability, statistics, or data science.
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A Bachelor's degree in subject areas such as Library Science, Linguistics, Mathematics, Statistics, Data Science, Computer Science, or other computer-related specialization.
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Develop innovative processes focused on natural language processing, data science, machine learning, and text analysis as we build the next generation of Bloomberg's proprietary news classification products.
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Bachelor's degree in data science, mathematics, statistics, economics, computer science, engineering, or a related business or quantitative discipline with 18 years of experience or Masters degree and 10 years of experience.
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The team focuses on the evaluation, analysis, design, debugging, and optimization of Google's storage, data analytics, and database platforms, and partners with Spanner, Bigtable, Sawmill Logs, Search Indexing, Napa, BigQuery, and Flume teams to drive performance optimizations and resource efficiency.
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Computer science, electrical engineering, electronic engineering, java, linux, optical, programmer, python, software. Involved in the analysis of unstructured and semi-structured data, including latent semantic indexing (LSI), entity identification and tagging, complex event processing (CEP), and the application of analysis algorithms on distributed, clustered, and cloud-based high-performance infrastructures.
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Experience working on data science projects and technologies, especially using NLP techniques to take care of unstructured text corpus. Understanding of a programming or query language and experience of using it for a data analysis (e.g. R, Python, JavaScript, SQL, etc.
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Work on design and implementation of best practices for Vector DB architecture, including data modeling, entitlements, indexing, and query optimization. A Bachelor's degree in computer science, artificial intelligence, machine learning, or related field.
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Build custom data pipelines to ingest data from third party data sources for our marketing and data science teams using Airflow and AWS resources. Knowledge of data warehousing concepts around building custom ETL integrations and building data infrastructure (SCD, CDC, Snapshots, indexing, partitioning.
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Provides technical expertise in database design tools and methodologies, data validation methodologies, data migration processes, file organization, indexing methods, data integrity, and security procedures, and backup and disaster recovery planning.
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Familiarity with at least 3 ServiceNow modules and applications, including: IT Service Management (ITSM) Database Skills: Strong understanding of database concepts, including: Data modeling and schema design Normalization and denormalization Query optimization and indexing Proficiency in database management systems, including: Relational databases (MySQL, PostgreSQL, etc.
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Metadata indexing, metadata summarization, content and metadata data mining, visualization and analytics. Bachelor's degree in System Engineering, Computer Science, Information Systems, Engineering Science, Engineering Management, or related discipline from an accredited college or university desired.
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PhD in Computer Science, Applied Mathematics, Statistics, Physics, or related quantitative field. MS/PhD in Computer Science, Applied Mathematics, Statistics, Physics, or equivalent work or industry experience.
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The Search and Browse Applied Data Science team builds the core relevance engine and Data Science products that power Target’s Digital experience. Research and/or demonstrated industry experiences in Search Indexing, Information Retrieval, Ranking as well as NLP, LLMs or Recommendation Systems.
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Bachelor’s degree in information management, computer science, or a master’s degree in library science or related field. Implement a taxonomy/ontology management system (TOMS) for indexing and leveraging unstructured content.
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indexing computer science data jobs
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