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Be fluent working with large, complex medical claims data using analytics technologies (SQL, SAS, Python/Pyspark, Databricks, Microsoft Azure, PowerBI) and analytics methodologies (exploratory/descriptive analysis, predictive modeling, causal outcomes research, and data visualization.
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Master's degree in Biostatistics, Statistics, Public Health, Data Science, or a related field and a Minimum of six (6) years of progressive corporate, non-profit, or consulting experience, including a Minimum of four (4) years in data analytics or directly related field.
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Bachelors and/or Masters degree in Actuarial Science, Mathematics, Statistics, Finance or a related field. Focus on loss reserving projects with additional engagements in pricing/ratemaking, predictive modeling, economic capital modeling, and loyalty rewards programs.
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PhD in subsurface geosciences or engineering, with background expertise that could include structural geology, reservoir geomechanics, petroleum engineering, fluid flow modeling, geophysics/seismology, or closely related disciplines.
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At least six years of experience in Data Science or Modeling for consumer lending, two years of leadership experience in highly quantitative teams; Professional experience waived with at least four years of Data Science or Modeling experience and Ph. D. Degree in highly quantitative field (Statistics, Economics, Mathematics, or other quantitatively oriented degree.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Masters degree in Biostatistics, Statistics, Public Health, Data Science, or related field and Minimum three (3) years experience in data analytics or a directly related field. Minimum one (1) year statistical modeling experience using SAS, R, or another advanced statistical package.
$96,800 - $125,290 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Computational biologist: Candidates should have expertise in computational biology, statistical modeling, machine learning, and artificial intelligence method development with a strong track-record of research in using data-driven approaches to study the molecular and physiological basis of cancer, including identification of biomarkers that drive cancer development and progression, as well as innovative approaches for drug discovery and novel therapeutics development.
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Strong data analysis and modeling skills using Python, SQL, VBA or R; a programming background preferred. Masters is preferred in a highly analytical or technical field: Computer Science, Engineering, Math, Statistics, Physics, etc.
ExpandApply NowActive JobUpdated 21 days ago - UpvoteDownvoteShare Job
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Proven advanced expertise in quantitative analysis, financial modeling, and data visualization tools (e.g., Excel, SQL, Python, Tableau). Requirements:Bachelor's degree in Finance, Economics, Statistics, or a related field; Master's degree preferred.
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Conduct research in machine learning, deep learning, and statistical modeling to design and implement new algorithms and techniques for multi-modal, generative AI, and LLM applications. Masters or Pursing Ph. D. in computer science, electrical engineering, statistics, or a related field, with a focus on machine learning, deep learning, or AI in general.
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Proven experience building and deploying models (FinTech/healthcare preferred), strong grasp of statistics, ML techniques, and cloud platforms (AWS, Azure, GCP), and containerisation expertise (Docker, Kubernetes.
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Part-Time Bilingual Chinese / English Academic Specialist TON: High Level Mathematics And Statistics
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AP and lower college level, for our high school and college tutoring programs: AP Statistics, Statistical Concepts, Statistics, Probability and Mathematical Modeling, Statistics and Data Analysis, Data Science, Business Statistics.
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Experience working with advanced statistics, machine learning, and deep learning including different architectures, embeddings, loss functions, and optimization strategies. Work experience in designing and managing data pipelines with knowledge about data modeling, ETL processes, and big data technologies (e.g., Spark) to support AI & ML on a public cloud platform, preferably MS Azure.
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Strong technical proficiency in data modeling, SQL, ETL tools, data visualization tools, and advanced analytics techniques (e.g., machine learning, predictive modeling). Drive the development and implementation of advanced analytics initiatives to extract insights from data, identify trends, and support predictive modeling and forecasting.
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Proven understanding of statistics, structured and unstructured data analysis, predictive modeling techniques and data visualization as well as a good command of emerging methodologies like Artificial Intelligence.
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