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Familiarity with data engineering concepts and tools such as data pipelines, ETL processes, SQL, and big data technologies (e.g., Apache Spark, Hadoop). We are seeking a skilled Sr. Martech Software Engineer with expertise in marketing technology platforms (CRM or CDP) such as Adobe Experience Platform (AEP) or similar (e.g. Salesforce, Dynamics, etc), coupled with strong skills in building custom solutions on AWS, proficiency in API development using languages like Python or Java, and some experience in data engineering.
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Examples include investigating how high-fat diets may promote liver cancer as well as the effects of near weightlessness on iPSCs in conjunction with NASA, connections among diabetes and chronic pancreatitis and pancreatic cancer, and the genetic underpinnings of disease, exploiting the potential of stem cells, leveraging nanotechnology, parsing big data, and assessing how gender and metabolism impact health.
$450,008 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Experience must include two (2) years of experience in data mining and development of ETL processes; distributed data architectures and big data processing technologies such as Spark, EMR, Hadoop and Hive; and Realtime Frameworks, collection, and processing Realtime data using kinesis Data Streams, KCL, KDA and Firehoses.
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The laboratory focuses on using big data approaches to neuroimaging and genetics, using behavioral and non-invasive MRIs to examine brain-behavior relationships after stroke. Technical knowledge of neuroimaging and brain anatomy, experience with organizing, maintaining, and analyzing large brain imaging datasets, programming expertise with python, Bash and parallel computing, experience with Brain Imaging Data Standards (BIDS) and MRI—based neuroimaging software programs (e.g., FreeSurfer, ITKSna) and statistics/machine learning strongly preferred.
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Stay abreast of emerging technologies and trends in martech, API development, cloud computing, and data engineering to drive innovation and improve martech capabilities. Utilize Python and other relevant programming languages to build robust APIs, microservices, and integrations for seamless data exchange and automation.
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4+ years of experience in big data and event streaming technologies: Spark, Kafka, etc. 2+ years of experience in cloud technologies: Azure (big plus), AWS, OpenStack, etc. Minimum of 4+ years of experience with databases and data modeling / design (SQL and NoSQL.
$172,355 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The Data Science program is where students learn to leverage the power of big data to extract insights and improve decision-making for real-world problems, gain hands-on experience in data management and visualization, machine learning, statistical models, and more for a career in data science.
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Big Data Technologies: Proficiency in Databricks, Spark, PySpark, Scala, and SQL. Data Engineering Fundamentals: Expertise in ETL/ELT processes, data pipelines, data modeling, schema design, and data warehousing.
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Create and implement supply chain strategy Demand forecasting and production planning Forecast demand trends based on a variety of data and business related factors Inventory management KPI monitoring and analysis of inventory turn, service levels, and accuracy of forecast Supplier and contract manufacturer relationship management Lead process improvement initiatives What is in this Demand Planning Manager role for you.
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Experience supporting Client models development on big data infrastructure (on knowledge graph would be a bonus). Have experience in building graph-based ontology from scratch and working with structured and unstructured data.
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We use cutting-edge technologies like AI, machine learning, cloud computing, and big data analytics to protect investors and ensure market integrity. Drive alignment and implementation of an enterprise-wide Data Governance operating model, ensuring a clear understanding of data ownership and stewardship with well-defined processes and roles.
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Familiarity with CI/CD, ETL, big data tools, and mainstream ML libraries (e.g., MapReduce, Spark, Flink, Kafka, Docker, Kubernetes, TensorFlow, PyTorch, Spark ML, etc. Solid theoretical background in machine learning or data mining and strong conceptual, problem-solving, and analytical skills.
$230,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Strong working experience with Big Data technologies (Spark, Data Bricks) for Data integration, & processing (ingestion, transformation, curation, etc), preferably on Azure cloud, and a clear understanding of how the resources work and integrate with cloud and on-prem.
$155,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Big Data Technologies: Proficiency in Databricks, Spark, PySpark, Scala, and SQL. Cloud and Data Engineering: 5 years of hands-on experience with Azure Data Factory, Databricks, API management, and managing Azure resources.
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Experience with mainstream big data tools (e.g., MapReduce, Spark, Flink, Kafka, etc. Solid theoretical background in machine learning and/or data mining. As a machine learning model engineer of the Samsung Ads Platform Intelligence (PI) team, you will have access to unique Samsung proprietary data to develop and deploy a wide spectrum of large-scale machine learning products with real-world impact.
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