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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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If the candidate does not have a background in Actuarial science, the candidate should have 4+ years of industry experience building and analyzing machine learning models and should hold a graduate degree in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics, Physics, Mathematics, Economics or Engineering.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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The scientist will work on a team with deep expertise in computational biology, data science, genomics, and pharma/biotech partnerships – with the unified goal of deriving maximal value from Caris’ data for external and internal research efforts to advance cancer care.
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In this role, you will support the successful development of data strategies, data governance programs, data modernization roadmaps, reporting and visualization tools, and craft business cases for funding of data initiatives at large corporations, in particular regard to EHS and ESG functions.
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Day to day you’ll be building ETL pipelines, modeling data to feed analytical reports and data science models, designing data access tools, or building data models in Looker.
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Upon successful completion of the program, you will have career opportunity as a Data Scientist, Data Engineer, or other roles at AGCO. Candidates who apply for this program, should be interested in a long-term career path with AGCO. By joining ACGO’s CATALYST rotational development program, you will discover the endless career opportunities through a solid foundation of data & analytics and understanding of our customers.
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Degree: Mathematics, statistics, computer science, data science or field directly related to the position. Manages multiple complex data analysis projects, using approaches common to the field of data science including AI/ML techniques, data visualizations, and other analysis supporting policy, supervision, and resolution planning related to large complex financial institutions (LCFIs) including banks, bank holding companies (BHCs) and other systemically important non-bank institutions with national or international operations.
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Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of experience as a Data Scientist, Data Engineer, or other occupation/position/job title involving research and data analysis.
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Senior Consultant - Payments Fraud Analytics and Data Science. Payments Fraud Analytics and Data Science Senior Consul. This include applying data science and technology skillsets when working with large-scale financial institutions, financial technology ("fintech") organizations, and other money service businesses.
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Drives strategic data sourcing and tooling projects to deliver new capabilities and tools in support of data science into the audit department, building use-cases, and repositories of data sources and re-usable data analytics products for the area of responsibility.
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This role will provide expertise to support the development of a Big Data / Data Lake system architecture that supports enterprise data operations for the District of Columbia government, including the Internet of Things (IoT) / Smart City projects, enterprise data warehouse, the open data portal, and data science applications.
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Our data analytics and software platforms support data science, commercial operations, real world evidence, and cloud information management. Lead and execute with full ownership of RWE studies/analyses by SAS/SQL/R/Python based on claim database, EMR database, registry data and public used files.
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Bachelor's degree in Statistics, Economics, Computer Science, Management of Information Systems, Data Science, Business Management, or related field. Apply data science, machine learning, network analysis, and other advanced approaches over large datasets to facilitate the detection of fraud and security schemes.
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Certifications in data science or cloud tools and technologies. Predictive Analytics/Data Mining: (e.g., Python, SAS Enterprise Miner) Data Visualization Tools (e.g. QlikView, Tableau, Power Bi.
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data science jobs Title: senior data engineer Company: Change Healthcare
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