Idaho Occupational Therapy Associaton
Data Science Developer
Idaho Occupational Therapy Associaton, Seattle, Washington, us, 98127
W-2 Open Positions Need to be Filled Immediately. Consultant must be on our company payroll, Corp-to-Corp (C2C) is not allowed.Candidates encouraged to apply directly using this portal. We do not accept resumes from other company/ third-party recruiters
Job OverviewSpecialized Area:Data ScienceJob Title:Data Science DeveloperLocation:Seattle,WADuration:12 MonthsDomain Exposure:Healthcare, Telecom, Education, IT/SoftwareWork Authorization:Client:To Be Discussed LaterEmployment Type:W-2
(Consultant must be on our company payroll. C2C is not allowed)Apply appropriate data reduction, feature selection, and feature engineering techniquesDevelop and implement hypothesis testsDevelop, validate, and operationalize appropriate mathematical and statistical algorithms and models; including implementation on large scale systemsReview, make enhancements to, and execute operationalized algorithms and modelsDevelop data products to communicate insights to business stakeholdersCollaborate with data & technology teams to create repeatable processes and scalable data products.Requirements:Minimum of 5-8 years proven business experience and technical expertise in data scienceExperience cleansing and preparing large, complex datasets for analysisExpertise applying statistics or machine learning in a professional or other intensive problem-solving environment with large, complex datasetsExperience with hypothesis testing, clustering, regression & classification, time series analysis, & optimizationExpertise in statistical programming languages such as R or the Python scientific stack (NumPy, SciPy, scikit-learn, etc.)Professional-level expertise in developing, validating, and executing algorithms and models on large scale systemsExperience with SQLExperience with Amazon Web Services (RedShift, S3, EC2, EMR, etc.) and Apache Spark preferredFamiliarity with data visualization applications, like Tableau or RShinySelf-starter with strong analytical, critical thinking, and problem solving skillsExcellent communication skills -- ability to present complex information in a concise and compelling mannerPrevious management of data science project execution and data scientistsPrior media or direct-to-consumer industry experience preferredMACHINE LEARNING TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. MACHINE LEARNING TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will MACHINE LEARNING 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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Job OverviewSpecialized Area:Data ScienceJob Title:Data Science DeveloperLocation:Seattle,WADuration:12 MonthsDomain Exposure:Healthcare, Telecom, Education, IT/SoftwareWork Authorization:Client:To Be Discussed LaterEmployment Type:W-2
(Consultant must be on our company payroll. C2C is not allowed)Apply appropriate data reduction, feature selection, and feature engineering techniquesDevelop and implement hypothesis testsDevelop, validate, and operationalize appropriate mathematical and statistical algorithms and models; including implementation on large scale systemsReview, make enhancements to, and execute operationalized algorithms and modelsDevelop data products to communicate insights to business stakeholdersCollaborate with data & technology teams to create repeatable processes and scalable data products.Requirements:Minimum of 5-8 years proven business experience and technical expertise in data scienceExperience cleansing and preparing large, complex datasets for analysisExpertise applying statistics or machine learning in a professional or other intensive problem-solving environment with large, complex datasetsExperience with hypothesis testing, clustering, regression & classification, time series analysis, & optimizationExpertise in statistical programming languages such as R or the Python scientific stack (NumPy, SciPy, scikit-learn, etc.)Professional-level expertise in developing, validating, and executing algorithms and models on large scale systemsExperience with SQLExperience with Amazon Web Services (RedShift, S3, EC2, EMR, etc.) and Apache Spark preferredFamiliarity with data visualization applications, like Tableau or RShinySelf-starter with strong analytical, critical thinking, and problem solving skillsExcellent communication skills -- ability to present complex information in a concise and compelling mannerPrevious management of data science project execution and data scientistsPrior media or direct-to-consumer industry experience preferredMACHINE LEARNING TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. MACHINE LEARNING TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will MACHINE LEARNING 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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