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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 7 days ago - UpvoteDownvoteShare Job
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Minimum 2 years of management and leadership experience Knowledge of Windows workstation platforms, Azure AD, Intune/Modern Management, GPO, Microsoft o365, Microsoft Endpoint Configuration Manager (formerly SCCM) Limited immigration sponsorship may be available Preferred Technical skills: Data Science / Analytics using a multitude of data sources.
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Graduate degree in Management Information Systems, Business Administration and Management, Business Analytics and Information Systems, Statistics, Mathematics, Computer Science, Physics, Economics or a similar degree.
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Currently pursuing a Bachelor’s degree in Computer Science, Statistics, Data Science/Analytics, Management Information Systems, Mathematics, Natural Science, Economics, Engineering or similar quantitative field and no experience and will obtain degree prior to first day of employment.
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Oversee the design, development, and management of scalable and reliable data engineering solutions that support data products deployment for use in advanced analytics, data science, and AI initiatives.
$248,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Desired Background PhD in Computer Science or related field 4-8 years of professional experience with relevant experience building and designing distributed data systems Knowledge of statistics, data science, AI/machine learning, big data management Strong proficiency in Python and an additional language (e.g., C.
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Demonstrated experience with big data processing systems and distributed computing technology such as Databricks, Spark, Sagemaker, Kafka, Tidal/Airflow, etc. How you will contribute:Be a leader of the RDQ data program that includes integrated data flows with end-to-end data management control mechanisms, internalization of enterprise systems, enablement of automation, near-time data access/streaming data sets, efficient data query review, and flexibly allow inspiring technologies for insight derivation.
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Bachelor's or Master's degree in a quantitative field such as Computer Science, Data Engineering or related discipline. Stay up-to-date with the latest advancements in data science, machine learning, and related fields, and apply them to improve existing processes and methodologies.
$135,240 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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With the power to apply artificial intelligence and data science to business decisions via enterprise data management solutions, we help leading companies prototype, refine, validate, and scale the most desirable products and delivery models to enterprise scale within weeks.
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Experience building and optimizing best practice Enterprise Risk Management, Third Party Risk Management, Risk Quantification, as well as Data Governance and Artificial Intelligence (AI.
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FIELD(S) OF STUDY: Data Analytics/Business Intelligence, Computer Science, Business Administration, Industrial Engineering, Mathematics, or related field. A minimum of 2 years of work experience in reporting, analytics, business intelligence, data science or similar field is required.
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Knowledge and proven use of contemporary data mining, cloud computing and data management tools including but not limited to Microsoft Azure, AWS Cloud, Google Cloud, hadoop, HDFS, mapr and spark.
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HPBIND Key Words: Campaign Strategy Lead Generation Customer Acquisition ROI Optimization Cross-Channel Marketing Performance Metrics Vendor Management Influencer Marketing Digital Marketing Content Optimization A/B Testing Team Leadership Budget Management Sales Funnel Management Audience Segmentation Brand Alignment Market Research Customer Engagement Creative Collaboration Marketing Automation Data-Driven Insights KPI Tracking Cross-Team Collaboration Marketing Analytics Powered by JazzHR.
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The Vice President, Information Technology, will be responsible for the strategic direction and oversight of our IT infrastructure, security protocols, and data architecture. Element Science, Inc. is a medical device and digital health company focused on developing solutions at the intersection of clinical-grade wearables, machine learning algorithms, and lifesaving therapies in order to address leading causes of death and hospitalization in patients with heart disease, primarily as they transition from the hospital-to-home.
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Collaborate with IT and data science teams to leverage big data and artificial intelligence in pharmacovigilance. Clinical Research, Clinical Trials, Leadership, Regulatory Compliance, Safety Science, Strategy.
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big data science management strategy jobs Title: vice president
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