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Master's degree in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field, or Bachelor's degree and 6+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience.
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Relevant skills include statistical analysis and open-ended data mining (social network analysis will be particularly helpful); applied machine learning including Natural Language Processing; quantitative content analysis; qualitative discourse analysis; survey research; and archival research.
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Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
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Skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
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Potential candidates should have a terminal degree in public health, epidemiology, health services research, biostatistics, data science or related fields. A Ph. D. in public health, epidemiology, health services research, biostatistics, data science, or related fields.
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Possess a minimum of 12 years of data mining and modeling experienceProficient in one or more of the following software platforms: Python, IBM SPSS Modeler, Natural Language Processing, Large Language Models, Generative AI Applications, and/or User Activity Monitoring applicationsAdvising stakeholders on advanced data mining and technical matters, research, and applications.
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PhD or Masters's Degree in Computer Science, Mathematics, or Statistics a similar technical field of study with a specialisation in Machine Learning, Data mining, Information Retrieval or Data science.
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The solutions developed draw on IT-RI’s strong capabilities in statistical modeling, machine learning, natural language processing, information retrieval, statistical genomics, data mining, and big data management and analytics.
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Candidates must have strong capabilities in relevant research methods, which could include social network analysis, statistical analysis and open-ended data mining; applied machine learning including Natural Language Processing and image recognition; interactive data visualization; and website development.
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Use advanced knowledge in machine learning, statistics, text mining, natural language processing, computational semantics, computer vision, and data science to develop creative solutions to complex real-world problems.
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Proving specialization background in data science, including experience with statistical analysis, data mining, predictive modeling, and machine learning; Demonstrating a thorough level of knowledge in statistical modeling, algorithms, data mining, and machine learning algorithms problem solving.
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Data Processing/Analytics/Science, Computer and Information Science, Statistics. The successful candidate will be responsible for leveraging their data science background to drive compliance monitoring data analytics initiatives.
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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)Primary Location.
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Utilizing data science techniques to analyze large data sets and identify patterns, trends, and anomalies that may indicate potential compliance violations; Demonstrating intimate knowledge about designing and implementing data-driven analyses to monitor for compliance with regulations and standards, such as anti-corruption laws, data privacy regulations, and industry-specific regulations.
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Demonstrating thorough knowledge about ETL tools and techniques, such as tools like Alteryx, Power Query, Azure Data Factory, and Power Apps suite of tools; Collaborating with cross-functional teams, including Finance, the Office of the Chief Data Officer, the Office of the General Counsel, Business Services Technology, Network Information Security, Internal Audit, and other firm functions to gather relevant data and establish data integrity for analysis.
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