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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch) Primary Location.
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Minimum of 5 years of experience in a Data Architect or Solutions Architect role with a focus on implementing cloud data warehouse (e.g. Snowflake, Databricks) solutions. Design Client generative AI powered software design lifecycle solutions for the identified use-cases across leading cloud data warehouses like Snowflake and Databricks.
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Experience with big data tools: Spark, Kafka, HBase, Hive, Impala, Presto, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS/GCP big data technologies.
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The ideal candidate will have a background in Azure Data Engineering, Azure Data Lake, Azure Databricks, MS Fabric Ecosystems and Oracle E-Business Suite (EBS). Design, develop, and implement data engineering solutions using Azure Data Services (Azure Data Factory, Azure Databricks, Azure Synapse Analytics, etc.
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BS / MS / PhD in computer science / computer engineering / biomedical engineering / electrical engineering / Data Science / Machine Learning background with 2/3 years of work experience. Experience in signal processing, time-series data analytics, digital health domain.
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What Additional Experience Makes A Strong Candidate: 4+ years of production experience with Scala 4+ years of production experience with Micro Services / Streaming Services Experience addressing ML problems, particularly in domains such as Time Series, Computer Vision (CV), Natural Language Processing (NLP), and data mining Proficiency with popular ML frameworks (Xgboost, TensorFlow, PyTorch, etc.
$275,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Specific responsibilities include: - Champion security: Follow best practices to meet the high standard of regulatory data security requirements. Data Security department of TikTok provides payment solutions - including payment acquisitions, disbursements, transaction monitoring, payment method management, foreign exchange conversion, accounting, reconciliations, and so on - to ensure that users have a smooth and secure payment experience on TikTok platform.
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Our Mission is to drive monetization and sustainable revenue growth for TikTok through data science. The successful candidate will gain an understanding of the data science techniques to power TikTok monetization and drive meaningful improvements in ads targeting and ranking models.
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Incident Management | Problem Managemen | FinTech | Banking | Data Analytics | SQL | Tableau | Monitoring Tools | Splunk | ServiceNow | ITSM | Operational Excellence | Customer Experience | Cross-Functional | Collaboration | Business Recovery | Program Management | Project Management | Small Business Banking.
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Deliver Master Data Dictionary and Enterprise Content Management Records Management, Taxonomy, Data standards, and practices framework. Experience with data management toolsets such as IBM IGC, Talend Data Catalog, Talend Data Fabric, Collibra, MS Purview, etc.
$209,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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The Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipelines based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle issues or provide recommendations for the next step in problem-solving.
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We sell the latest AI technologies from Nvidia, Supermicro, Dell, HP, Microsoft, Google, Cisco, Lenovo, Apple, VMWare, Adobe, APC, IBM, Nutanix, EMC, Pure Storage, Samsung, Intel, Eaton, and all the hottest AI and Green Data Center, Virtualization, Energy Conservation, Cloud, Storage, Security, Wireless, SD Wan, Video, Identification, solar, and battery technologies.
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Work closely with photonics, electronics, and test engineers on data-driven circuit design and analysis, focusing on photonic switching networks. We know that means it will need 1 million qubits, error correction, a scalable architecture and a data center footprint.
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Data Pipeline Construction: Engineer robust data pipelines that are capable of handling large-scale data sets typical in the automotive industry, ensuring data integrity and speed.
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Professional Certification & training in related fields e.g. CCNA/CCNP, Fortinet, Palo Alto, Juniper, Data Center, Microsoft, VMware, etc. Job Responsibilities Solution Coverage: Networking Solutions (Active, Passive Network), Network Security Solutions, Data Center, Server & Backup Storage Solutions, Cloud & Hosting solutions, Email Server & Security Solutions, Virtualization Solutions, Access Control, Surveillance, IP PBX, IT Enabled Services etc.
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data job Title: operator in Palo Alto, CA
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