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Continue to develop and help drive the strategy for the organization's data strategy including data architecture, Reporting, Insights, Analytics, Operations, Predictive modeling, attribution and Machine Learning/AI.
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Experienced in using multiple data science methodologies to solve complex business problems (e.g. statistical analysis, research science, machine learning and deep learning techniques, data modeling, regression modeling, financial analysis, demand modeling, etc.
$90,000 - $120,000 a yearFull-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Strong knowledge of statistical analysis, predictive modeling, machine learning, and optimization techniques. Develop and implement algorithms for data analysis and modeling. Proficiency in programming languages such as Python, R, or SQL, and experience working with big data platforms and tools (e.g., Hadoop, Spark.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Alternative education and experience required: Bachelor's degree in Data Science, Machine Learning, Software Engineering, Statistics, Operations Research, or related field and 8 years of progressive, post-baccalaureate experience as Data Analyst or Scientist, Machine Learning Engineer, Statistician, Business Analyst, or related role.
ExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Preferred Qualifications: Experience implementing and designing attention-based or transformer-based modeling (e.g. State of the art NLP and Vision models or any other sequence to sequence-based DL models.
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The Senior Lead Data will be responsible for partnering with Technology, Machine Learning, Product Architecture, and other Capital One teams to support the development of the Finance Tech Data Strategy into products and services we create and consume.
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Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across dating, personalization, growth, discovery, ads and search. Be an expert in matching algorithm and recommender systems machine learning models and own the implementation of dating recommendations in Grindr.
$160,000 - $220,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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The Financial Crimes Data Science Manager is primarily responsible for leading the development and validation of predictive and machine-learning models for specific business needs using statistics, advanced mathematical techniques, and/or computer science.
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One (1) year of 3D CAD design (e.g. Solidworks, AutoCad Inventor, Pro/Engineer) that includes modeling and automation systems design experience. A strong precision machine design background.
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We're seeing candidates who are excited at the prospect of unlocking the secrets held by a data set, and you're fascinated by the possibilities presented by advanced data modeling, machine learning, and artificial intelligence.
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Responsible for calculating and entry of individual patients' dialysis machine programming for Ultrafiltration (UF) goal; treatment time; Sodium (Na) modeling; and UF modeling as prescribed.
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Cleans and disinfects dialysis machine surfaces, chair, equipment, and surrounding areas between treatments according to inpatient renal services policies. Performs all required pre-treatment dialysis machine alarm testing, including Pressure Holding Test (PHT) and Diasafe test.
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This team is responsible for Global Customer Personalization products which including batch/real-time analytical, machine learning and modeling solutions using technologies such as Hadoop, Spark, HDFS, MapReduce, Hive, HBase, Python & Java. This young team has delivered industry leading products with many firsts in the organization.
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The Data Scientist will be responsible for leveraging data, advanced quantitative modeling, financial analysis and cloud-based machine learning technology to enable data-driven strategic decision making.
Full-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Experience with machine learning, natural language, and statistical analysis methods to include classification, collaborative filtering, association rules, sentiment analysis, topic modeling, time-series analysis, regression, statistical inference, and/or validation methods.
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