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You will work directly with our Chief Technology and Product Officer and Chief Economist who are building a foundation in tech AI solving problems for fortune 500 companies using applied economics and data science.
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Recent PhD degree in statistics/biostatistics, applied mathematics, infectious disease epidemiology, population biology, theoretical ecology or a similarly quantitative discipline. The successful applicant will be joining a dynamic multi-disciplinary group to work on development, refinement, and utilization of different classes of epidemiological models as well as application of methods for effective model configuration and calibration using data collected by the HIV Prevention Trials Network (HPTN) and by HIV Vaccine Trials Network (HVTN.
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M.S., or PhD. in Machine Learning, Statistics, Computer Science, Applied Mathematics or other related quantitative fields. As a Machine Learning Engineer, you will have the opportunity to leverage our robust data and machine learning infrastructure to develop inference and ML models that impact millions of users across our three audiences and tackle our most challenging business problems.
$255,800 a yearFull-timeExpandApply NowActive JobUpdated 2 months ago - UpvoteDownvoteShare Job
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Masters degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics or equivalent experience. PhD degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
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PhD in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field. Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
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You will be part of an integrated technical team and should be collaborative in nature, with expertise in applied data and machine learning science working along engineering teams putting your models into production.
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We are open to hiring candidates to work out of one of the following locations:Seattle, WA, USABASIC QUALIFICATIONS- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 6+ years of applied research experience- 4+ years of building machine learning models for business application experience- Experience programming in Java, C.
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Knowledge of big data/advanced analytics concepts and algorithms (e.g. text mining, social listening, recommender systems, predictive modeling, etc.) Execute statistical and data mining techniques (e.g. hypothesis testing, machine learning and retrieval processes) on large data sets to identify trends, figures and other relevant information.
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3+ years of experience building, mentoring and growing a team of Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists. Master's degree in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent.
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Job Title: Data Science Manager. Specialized Area: Data Science. 6+ years of experience developing statistical models and machine learning software in a language like Python, R, or Java to drive significant business impact.
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Data Science Manager. Nor will AUTOMATION TECHNOLOGIES LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract.
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Use machine learning and predictive modeling to develop data-driven solutions that drive substantial business value to the external consumers and internal stakeholders/partners. Work to instill data best practices around the organization.
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Master or PhD degree in a quantitative field such as statistics, applied math, operations research, economics or engineering (advanced degrees preferred). As a Data Scientist, Decisions in the Rider team, you will leverage data and rigorous, analytical thinking to shape our rider app and make business decisions that put our customers first.
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Bachelor's or Master’s degree in Statistics, Applied Math, Operations Research, Economics, Engineering or a related quantitative field with 5 years of working experience as a Data Scientist.
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Experience with Bayesian statistical methods of model calibration or longitudinal data analysis is a plus. With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world’s leading cancer, infectious disease and biomedical research centers.
$140,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago
applied quantitative data jobs in Seattle, WA
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