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Stationed in our global offices, AAG team members hold advanced degrees in computer science, engineering, AI, data science, physics, statistics, mathematics, and other quantitative disciplines, with backgrounds in a variety of fields including tech, data science, marketing analytics and academia.
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Experience with any MPP data warehouses e.g. Snowflake, Big Query, Redshift etc. Experienced on Big Data platform like Hadoop, hbase, CouchDB, hive, Pig etc. 5-7 years of experience as a Data engineer with extensive working experience using Pyspark, Advanced SQL, Snowflake, complex understanding of SQL and Skills, Spark, Snowflake and Glue.
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This individual will work directly with the Data Architect, along with the CTO of Lasso to establish a Machine Learning platform along with best practice engineering standards to ensure secure and successful data solutions.
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Experience in Big Data technologies/frameworks like Apache Kafka/Apache Spark/NoSQL databases. We develop cutting-edge ad campaigns serving and monitoring platforms, big data real time and batch processing systems.
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Center 3 (19075), United States of America, McLean, VirginiaPrincipal Data Scientist - NLPAt Capital One, we think big and do big things. Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics.
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The future of biology is in big data analysis, and we are on a mission to accelerate digital drug discovery with the Watershed platform. We have attracted some of the best bioinformatics, engineering, and commercial talent, and we are growing.
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The Director, Clinical Project Management works cross-functionally with the Epidemiology, Biostatistics, Clinical Informatics, Engineering, and Data Science teams to drive the scoping and execution of new projects.
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Apply knowledge of Natural Language Processing, Big Data/Cloud technologies, Relational databases, CI/CD Development environments and tools, and Agile development methodology. Perform data collecting, preprocessing, feature engineering, data visualization and analysis.
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Position SummaryThe Data and Software Engineering team in Cambridge, MA is looking for a Full Stack Software Engineer with a passion for solving big problems, a desire to make a real difference immediately, and a drive to continuously learn new technologies in software, data, and biotechnology.
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Technology Analytics - Packages Python - Big Data, Technology Cloud Integration Azure Data Factory (ADF), Technology Data on Cloud-DataStore Snowflake. Strong knowledge of Data structures, Data Engineering concepts, Algorithms, Collections, Multi-threading and memory management and concurrency.
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Experience with Big Data technologies (Snowflake, Databricks/Spark, Trino). Has knowledge of data engineering best practices (data discovery, data documentation, infrastructure development/deployment, and information security.
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To best utilize our data assets and spur innovation, we have built our own extraordinary in-house big data capabilities - we think as good as any in Silicon Valley - populated with more than 200 analysts and data scientists, which we call Intelligent Solutions," Dimon wrote.
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Practitioner experience in multiple data technologies such as: Cloud Data Platforms (AWS, Azure, Google Platform, Databricks, Snowflake) Big Data applications and Distributed Processing (Hadoop and Spark ecosystem components) Data integration Tools (Informatica, Talend, etc.
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Familiarity with cloud platforms (e.g., AWS, Google Cloud) and big data technologies (e.g., Hadoop, Spark). Work with our data engineering team to develop and maintain data pipelines, ETL processes, databases and data warehouses for the firm’s workplace data.
$220,000 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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At 1910 Genetics, we put computation at the heart of drug discovery, blending expertise in computational chemistry, structural biology, pharmacology, genetics, data science, and software engineering to develop drugs for previously undruggable targets.
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