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Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support the development of health policy.
$122,100 - $234,700 a yearFull-timeRemoteExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Data science, Python, Machine learning, Predictive modelling, Predictive analytics, NLP, Azure, Databricks, Snowflake, Linux. Data science,Python,Machine learning,Predictive modelling,Predictive analytics,NLP.
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As a Research Data Scientist II, you will utilize statistical and machine learning techniques, high performance data architectures and technologies to build algorithms and perform data analytics, and programing skills, in languages such as SAS, SQL, SPSS, R, Python or similar, to work effectively with relational databases.
$36.8 - $56.13 an hourFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Knowledge of machine learning and AI methods and proficiency with scripting and executing data analytics algorithms and models with hands-on experience using a modeling and simulation software (e.g. Python, MATLAB, R, NONMEM, SAS, S-Plus, etc) is a must.
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Typical role includes working on a wide range of activities such as working with complex structured and unstructured datasets, developing/recommending novel machine learning tools, data visualizations, automation of analytics workflows, disease progression models, mechanistic and empirical PK/PD models, clinical trial simulations, literature meta-analysis using quantitative approaches and statistical modeling of historical and preclinical data.
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Adapt data science algorithms (supervised and unsupervised learning, decision trees, neural networks, AI based image processing and feature extraction, Bayesian learning, etc) for modeling clinical trial data to support drug development.
Full-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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This high performing team works with clients to implement the full spectrum of data analytics and data science, from data querying and data wrangling, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence as well as robotic process automation (RPA.
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As a Staff Data Scientist, you will utilize your expertise in data mining, predictive modeling, machine learning, and NLP techniques to drive strategic decisions for WCS. You will be at the forefront of implementing models and strategies using A/B testing or Design of Experiments (DOE), tracking business performance, and providing insightful visualizations to support and continuously improve WCS business strategy.
Full-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Ideal candidate is pre-ACAS through new FCAS with 4+ years of P&C actuarial, data science, or predictive modeling experience, including Machine Learning using SQL and Python (including pandas.
Full-timeRemoteExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Use of advanced analytics technologies, including machine learning and predictive modeling. AI, machine learning, deep learning knowledge, big data. Work in various projects/therapeutic areas: neurosciences, oncology, in vivo and in vitro research activities, genomics, patient follow-ups, safety and risk management, etc.
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The candidate is expected to be able to integrate modeling and simulation results into cross functional interactions, regulatory filings, and their application to dose selection, study design, risk/benefit, and advising drug development decisions in close collaboration with other R&D partners.
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This work will be performed in close collaboration with pediatric neurologist and epileptologist clinician researchers and faculty at NCH.The candidate should be able to leverage both structured and unstructured data sets to create analytical solutions using tools and/or methods in at least one of the following areas: statistical and predictive modeling, machine learning, natural language processing, and geospatial analysis.
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2 years of experience must include: Python; R; SQL; Hive; Tableau; Statistical modeling: linear and logistic regression; Machine learning techniques: Support Vector Machines and Random Forrest; and Exploratory and advanced data analytics.
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Conduct predictive modeling using statistical and machine learning techniques to answer business questions and inform strategic decisions. Develop predictive models using appropriate statistical and machine learning techniques.
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Perform data exploration using a combination of statistical programming languages (including, but not limited R, Python, SQL, SAS) and deploy predictive analytics and machine learning techniques to improve risk prediction, improve reserve, trend and financial forecasting in a manner that is actuarially sound, and enable real-time results and operational efficiencies.
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