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Apache Hadoop or Apache Spark (for big data processing) Natural Language Processing (NLP) Tools and Frameworks (e.g., Hugging Face, AWS Comprehend Medical for extracting insights from clinical text data.
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Master's degree in data science, computer science, statistics, computational linguistics or engineering preferred. Conduct advanced quantitative research, using machine learning (ML) and natural language processing (NLP) techniques to understand patterns in large volumes of data, identify relationships, detect data anomalies and classify data.
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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Minimum of 5 years of technical experience and 3 years of experience specifically in data science and machine learning. Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.
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About the Opportunity: Reporting to the President of World Science U (WSU) and Executive Director of Education, or in their absence, the Director of Education, the WSS program Manager oversees daily operations of the WSS program, working intimately with world-renowned scientists and coordinating with the WSF media team to produce and film high quality courses.
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Prior experience with Radiology Information Systems, PACS, Data processing and digital data transfer process. Registered X-Ray Technologist by American Registry of Radiologic Technologists (ARRT.
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Center 1 (19052), United States of America, McLean, VirginiaCurrent PhD - Data Science Internship - Summer 2025Key Role DetailsThis is a full-time paid internship program spanning ten weeks from June through August 2025.
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Ability to migrate the Data Science models written on native python language to the multi node Databricks compute. Seamless integration with On-prem databases and Power BI reports Build large-scale batch and real-time data pipelines with data processing frameworks in Azure cloud platform.
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Ensure high operational efficiency and quality of the Data Capture platform datasets to ensure our solutions meet SLAs and project reliability and accuracy to all our stakeholders (Engineering, Data Science, Operations, and Analytics teams.
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Preferably a master's degree related to Intelligence Studies, Forensic Science, Security Studies, Computer Science, Cybersecurity, Data Analysis, or a related field. Behavioral Science/ Behavioral Analysis/Behavioral Threat Assessment experience or training.
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Data Engineer (Full Time) Experience developing with data SaaS and BI tooling (Fivetran, Looker, dbt, Databricks, Apache Airflow, etc.) This includes new features and architectural improvements for our data pipeline and analytics tools, such as Looker, dbt, Databricks, Fivetran, Airbyte, and AWS Redshift.
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Familiarity with analyzing high-throughput genetic data is preferred (e.g., processing FASTA, BAM/CRAM, VCF, BED/BIM/FAM files using PLINK, bcftools, Hail); Ph. D. in Biological Sciences, Genetics, Statistics, Biostatistics, Computational Biology, Bioinformatics, Computer Science, Epidemiology, or equivalent.
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Collaborate across multidisciplinary teams—Compliance, Data Science, Model Risk Management, Data Governance, and Human Resources. This position reports to the Head of Fair Lending and works closely with the Head of Data Science, Fair Lending Compliance, and Model Risk Management to establish and lead a comprehensive and robust Fair Lending Analytics function.
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Data Ingestion to one or more Azure Services - (Azure Data Lake, Azure Storage, Azure SQL, Azure DW) and processing the data in Azure Databricks. Should be able to demonstrate expertise in designing and building efficient and scalable data engineering solutions using Massively Parallel Processing (MPP) architecture.
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About The Manager - Risk Finance Data Science Role. The primary responsibility of the team is to leverage data, latest tools, and advanced techniques to innovate and help the organization make sound forecasts of the company’s Billed Business and Loan amounts for all of AXP in the context of the annual Comprehensive Capital Analysis and Review (CCAR) exercise.
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data science processing jobs Title: engineer interface in New York
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