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Demonstrates knowledge of post-educational, private sector work in the financial services or bank regulatory areas required, including: Prepayment, credit risk, fair lending, default, Basel or fair lending modeling/modeling validation, advanced statistical and/or econometric modeling techniques and complex Excel-based spreadsheet models Statistical modeling assessing strengths and weaknesses.
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This individual will have a background in I/O Psychology and be skilled in psychological theory, scientific research methods, survey design, advanced statistical analysis, and data visualization.
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The candidate will support the Head of Statistical Programming to continuously improve processes to conform to evolving industry standards and participate in the ongoing review and development of quality systems and processes, including CDISC implementation and other internal/external initiatives.
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Verve is seeking a highly motivated and talented Scientist with experience in implementation, evaluation and application of statistical methods for the analysis of next generation sequencing (NGS) data to join our Computational Biology team.
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Develop models leveraging statistical analysis, regression modeling, optimization, predictive modeling, simulation, machine learning, economic models. Knowledge of analytical models, methods, applications and tools, such as statistical analysis, regression modeling, predictive modeling, simulation, machine learning and selecting and applying the right analytical techniques.
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Be accountable for statistical activities in support of IND/NDA/MAA or other regulatory submissions Address statistical questions/comments from FDA, EMA, and other regulatory agencies, and review and address comments by IRB/ECs.
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The Manager of Statistical Programming must effectively interface with Statistics, Data Sciences, Medical Writing, Regulatory Publishing and Clinical Operations. The Manager of Statistical Programming is a strategic role which guides a team of Statistical Programmers in the research and development of new pharmaceutical products.
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The Data, AI and Genome Sciences (DAGS) department is currently seeking a bioinformatician/computational biologist/statistical geneticist with extensive expertise in large-scale whole exome/whole genome data analysis to join an energetic team of computational biologists.
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Expert level fluency in statistical programming using Python, R/bioconductor or equivalents. Ph. D. in a computational, statistical, biophysics, or bioinformatics related fields. Synthesize our data into actionable insights by supplying to the Translational teams any needed computational, statistical, machine learning or modeling capabilities needed to advance our clinical programs.
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For example, multivariate analysis; dimensionality reduction methods; parametric and non-parametric statistical methods; Bayesian statistics; pattern recognition or classification methods. Assessment of treatment effects from both RNA (e.g., bulk, single cell, TCR/BCR, and spatial) and protein modalities (e.g., CITE/REAP-Seq, mIF, and high dimensional flow cytometry.
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BS + 4-8, MS + 3-5 or PhD + 0-3 years experience in statistical genetics, computational sciences (eg, computational biology, molecular biology), or related fields. As a Senior Data Scientist on the Statistical Genetics team in the Translation Data Science Group, you will contribute to building a computational platform that will change the way we identify and validate drug targets.
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The analyst /fellow may be responsible for the following activities: collecting, entering, and organizing patient data; cleaning and analyzing large databases of patient data; developing and running scripts and code to support research studies, generating data visualizations using statistical software including Python and Matlab; contributing to the preparation and presentation of research results in the form of oral presentation at meetings and conferences and in the form of publications.
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Proficiency in statistical methods for analytical assay performance, qualification, and trending. Proficient in molecular and cell based analytical methods including cell culture, In vitro cell based assays, ddPCR, ELISA, and flow cytometry.
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Proficiency in Microsoft Office, Google applications, Adobe Creative Suite, website management, live streaming, and statistical software. The Director is responsible for the overall operation of the Sports Information office, including the internal and external department communications and ensuring compliance with all NCAA and conference policies and procedures related to sports information, statistical reporting, and game management.
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Overseeing or acting as intermediate between Data Management, Statistical Programming and external data provider regarding external data specifications, data, and technical issues. Experience in technologies such as Medidata modules (RAVE, Coder, RTSM, eCOA), Veeva eTMF, eClinical Solutions Elluminate, SAS LSAF.
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statistical job in Boston, MA
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