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Ascend Performance Materials Holdings, Inc. in Houston, Texas seeks Data Science Manager (IT Business Manager). Analyze data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
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Preferred: Master's or PhD in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.
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This commitment is brought to life in the Institute for Data Science in Oncology (IDSO), a flagship program designed to reshape patient experiences and fast-track scientific breakthroughs via data-driven cancer care methodologies.
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The Lead Data Scientist at The Friedkin Group (TFG) will spearhead the design, development, implementation and maintenance and improvement of advanced data science initiatives across business units, directly aligning with strategic objectives.
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As a member of our Low Carbon Solutions Data Science & Analytics team, you will work on problems in emerging technologies such as carbon capture and storage, hydrogen, sustainable lithium extraction, or advanced biofuels.
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Bachelor’s Degree in Geology, Hydrogeology, Soil Science, Environmental Science or closely related discipline. Provide guidance with data collection efforts for extracting, identifying, and compiling environmental data from soil sampling, soil gas sampling, groundwater sampling, stormwater sampling, boring logs, and other matrices for projects, investigations, and surveys.
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Learns about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics as necessary to carry out role effectively. Experience with designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks, or distributed databases, like Redshift and Snowflake, and experience with housing, accessing, and transforming data in a variety of relational databases.
ExpandApply NowActive JobUpdated 12 days ago - UpvoteDownvoteShare Job
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Education: A higher education degree (MSc or PhD level) in fields such as economics, engineering, mathematics, computer science, statistics, applied physics, meteorology, or equivalent. Statistical Background: Proficiency in statistics and machine learning techniques, particularly when applied to meteorological data.
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A PhD (or equivalent experience) from Mechanical Engineering, Aerospace Engineering, Computer Science, Chemical Engineering, or Electrical Engineering with a focus on Control Theory and Applications, Robotics, Mechatronics, Machine Learning, or Data Analytics.
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PhD in quantitative scientific field: Mathematics, Computer Science, Data Science, Biomedical Engineering, Medical Physics, Physics, or Electrical Engineering. Background in algorithm development and implementation, medical image processing, image processing with artificial intelligence, X-ray physics, Computational Photography, and software development.
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PhD or other Doctoral Degree in cognitive science, educational psychology, education, educational data mining, or equivalent. We have created software to help college students in three of those subjects read with more engagement and practice more effectively, incorporating our research team’s expertise in cognitive science and machine learning.
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Our team is dedicated to identifying and interpreting genetic signal at the scale of thousands of phenotypes and millions of individuals, making the knowledge gleaned from genetics accessible to AbbVie's R&D community, and using data science and machine learning to maximize the value genetics brings to AbbVie.
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Common data science tools such as Python, R, Pytorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modelling platforms (Azure AutoML, SageMaker, DataBricks, DataRobot and H2O.ai.
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Our areas of expertise include remote sensing, geospatial analysis, GIS, soil science, water quality and demand evaluation, agricultural systems, salinity and nutrient management, ecosystem restoration, statistics, and regulatory policy.
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Familiarity with Information Governance technology ecosystem and how it supports Information Governance processes including: enterprise content / document management systems, records management systems, archival systems, legal hold management systems, mobile device management systems, communication surveillance applications, privacy compliance management systems, data discovery and scanning, etc.
$116,200 - $213,000 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago
data science jobs Title: data lead in Houston, TX
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