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Experience with Big Data frameworks (e.g. Hadoop MapReduce, Spark, Hive, Kafka) Expertise with Google Cloud Platform’s distributed Machine Learning, Data Science and Data Engineering tools (e.g. BigQuery ML, VertexAI, AutoML, Docker, Kubernetes, Kubeflow, Dataproc.
$140,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Architect and implement big data processing solutions using Databricks, leveraging Apache Spark for data transformation, ETL processes, and machine learning workflows. Proficiency in Databricks, Apache Spark, and related big data technologies.
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Knowledge of big data processing and analytics tools on gcp like bigquery dataproc experience in big data processing and analytics tools on gcp like bigquery. Our areas of expertise include application modernization ecommerce uxui design product strategy data analytics and artificial intelligence.
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Develop and optimize Databricks notebooks for big data processing and analytics in Azure Databricks environments. Expertise in SQL Server Management, Azure Data Factory Development, Databricks Engineering, Delta Parquet File Management, and SQL Server Integration Services.
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Work from Home Online Computer Work - Administration, Data Entry & Short Studies/Feedback - Part Time & Full Time Work - No Experience Needed, Training Provided. Salary: Data Entry Work from Home - Part Time Computer Job.
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Data Architecture & Tools: modern cloud data platforms (Snowflake, Databricks, Big Query, RedShift), data analytics tools (Tableau, Looker, Power BI), data programming models (DataFrames, pandas), and AI (Python, R, Jupyter Notebooks, data wrangling, machine learning.
$217,200 a yearFull-timeExpandApply NowActive JobUpdated 24 days ago - UpvoteDownvoteShare Job
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As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Develop and maintain expertise on the latest technologies relating to cloud, IoT, big data, and artificial intelligence to provide thought leadership to our prospects, customers, and within the company.
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The firm is the No. 1 investment bank for global M&A transactions under $1 billion, the No. 1 M&A advisor for the past eight consecutive years in the U.S., the No. 1 global restructuring advisor for the past nine consecutive years, and the No. 1 global M&A fairness opinion advisor over the past 25 years, all based on number of transactions and according to data provided by Refinitiv.
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In depth knowledge of modern data technologies including Snowflake, RedShift, Azure SQL/Synaspe, Databricks or similar technologies. Extensive experience or knowledge of data visualization technologies such as Tableau, Power BI, Qlik and Spotfire.
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Extensive experience or knowledge of cloud-based data platform technologies such as AWS, Microsoft Azure or Google Cloud Computing. Conduct data management maturity assessments and identify pain points for including data quality, governance, architecture, analytics, metadata management, master data management.
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We're helping patients get the best care possible by working on digital health experience, analyzing big data to streamline the delivery of care, and reaching out to medically complex patients to better understand their needs.
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Support vendor risk management and DPIA programs to ensure third parties comply with the Firm's privacy and data protection requirements. This role requires Data Loss Prevention (DLP) program experience, including conducting investigations related to data loss, data exfiltration, or unauthorized access or use of data, or experience using eDiscovery solutions or similar technology.
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Exposure to cloud platforms and big data systems such as Hadoop HDFS, Hive is a plus. Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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Data : Apache Spark, Kafka, Redshift, Snowflake. As the Delivery Manager, you will be responsible for overseeing the successful delivery of complex technology projects with a focus on AWS, DevOps, Data Engineering, and Generative AI solutions.
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