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Required: Master of Science (with 5 years of experience) or entry-level Doctorate in the computational and data sciences including statistics, artificial intelligence, biostatistics, bioinformatics, and statistical genetics.
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Strong fluency in Python and SQL, experience with Tensorflow, PyTorch, Airflow and data warehouse. Strong experience with Python/R, forecasting methodologies, machine learning and statistics.
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Programming: Languages: Familiarity or proficiency in languages commonly used in data science, like Python, R, or Scala. Data Visualization: Visualization Tools: Libraries like Matplotlib, Seaborn (Python), ggplot2 (R), or tools like Tableau, PowerBI. Data Interpretation: Ability to interpret visualizations and convey findings.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
$156,000 - $312,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The Associate Director of Quantitative Science is a self-sufficient and high-impact position that focuses on supporting the statistical and data science needs in the risk-based monitoring (RBM) of clinical trials, serving in roles such as CSM lead (CSM: Centralized Statistical Monitoring), while also support other activities such as preclinical studies, biomarkers, application of AI/ML and development of analysis applications.
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Proficiency in one or multiple literate statistical programming languages like R, Python, or Scala. 2+ years of professional experience in a data science role with an MS or PhD in STEM with a focus in ML, statistical modeling, or optimization.
$94,400 - $120,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Typically, Minimum 4 Years Relevant Exp Demonstrated experience with sophisticated analytics tools and programming languages (e.g., SAS, SPSS, R, Python, SQL, HiveQL, Spark, Hadoop) Proficiency with visualization platforms such as Tableau, Qlikview, PowerBI, D3, or JavaScript.
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Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Fluency in one programming and one scripting languages is required (Python, R/Matlab/Splus, Perl, Java) 2. Seeking a talented and highly motivated Bioinformatics Research Scientist to develop, optimize, and implement data analysis pipelines and analytical tools that enable comprehensive tumor genomic profiling for cancer biology research and cellular senescence biomarker discovery.
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Experience with Quantum Metrics and Akamai, Technologies and languages: Python, Spark, R, etc. Engineering, Data science or another quantitative field (i.e. mathematics, statistics, economics, etc.
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Advanced user of spreadsheet software (e.g. MS Excel), statistical tools (e.g. R, Python), and data visualization tools (e.g. Tableau, Power BI) to create data visualizations (charts, tables, infographics, presentations, and other visual productions) that help audiences understand results.
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Use Python/R and a modern data science stack (dbt, AWS, Docker, Gitlab) to ensure that solutions are reproducible, extensible, and easily integrated into the ATLAS data platform.
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The student will implement Python and other programming languages (e.g., MATLAB, R) to prepare and analyze data generated from several characterization techniques, such as differential scanning calorimetry (DSC), thermomechanical analysis (TMA), dynamic mechanical analysis (DMA), and mechanical testing.
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Demonstrated expertise working with R (preferred), python or STATA. Experience with enterprise databases and ETL tools (e.g., Databricks) Experience with data visualization software (e.g., Tableau, Power BI) is an asset.
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Proficiency using data analysis software (e.g., SAS, SPSS, R, Python, DeDoose, NVivo, ArcGIS, etc. For this role, Cadmus seeks candidates with professional experience in program evaluation, social science research methods, and/or energy efficiency or sustainability.
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