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The IDEA Project enables the development of modern data architecture to support descriptive, diagnostic and predictive analytics through the utilization of Informatica for data management and governance and Snowflake Data Cloud for optimized data storage.
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Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence.
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The postdoctoral researcher will use first principles modeling, molecular dynamics, and AI assisted methods to perform simulations/predictive analytics of materials and molecules to understand electrochemical processes and surface chemistry.
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Monitor and report on HR analytics trends, emerging technologies, and innovative practices to enhance HR data capabilities. In this role, you will have ownership of building out our People Analytics capabilities through leveraging data and analytics to provide insights and support strategic decision-making related to workforce management.
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Our high-performing team works with clients to implement the full spectrum of data analytics and data science, from data architecture and storage to data engineering and querying, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence.
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Proving specialization background in data science, including experience with statistical analysis, data mining, predictive modeling, and machine learning; 6 year(s) of experience in data analytics with a focus on Ethics & Compliance is preferred.
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Demonstrating a thorough level of knowledge in data analytics tools and programming languages, such as Python, R, and SQL; Data Processing/Analytics/Science, Computer and Information Science, Statistics.
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Lead portfolio segmentation efforts to help inform resource & capital allocation, such as redevelopment and capital recycling opportunities; incorporate predictive analytics where applicable.
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The LCRR Regional Lead will work closely with the Specialized Solutions group to apply dashboarding capabilities, advanced data analytics, and machine learning for predictive modeling of SL material identification but will not be responsible for development of these tools.
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The successful candidate will be responsible for leveraging their data science background to drive compliance monitoring data analytics initiatives. This Senior Manager will play a critical role in confirming compliance with ethical standards and regulatory requirements through the use of advanced data analytics techniques.
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Experience with machine learning algorithms and AI, including the use of frameworks to apply predictive models and advanced analytics within data engineering projects. A minimum of 5 years of experience in analytics engineering or data engineering, with a significant focus and hands on experience on data modeling and warehouse development.
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Experience working with multiple database platforms, such as SQL Server, MySQL, Oracle, DB2, Netezza, and IMS DB.Proficient in programming languages, such as SQL, PL/SQL, Java, Python, Cobol, and JCL.Understanding of data governance policies, procedures, and standards, including those for securityUnderstanding of APIs and other integration technologiesExperience with business intelligence and reporting platformsUnderstanding of machine learning and predictive analytics.
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Defines advanced analytics, M/L and AI project objectives, collaborates with the business for requirement, defines metrics and measures of effectiveness, and expected outcomes; identifies and/or develops innovative and effective approaches and methodologies; applies advanced operations research and data science techniques for quantitative analysis, statistical analysis, forecasting, predictive modeling, prescriptive analysis, and optimization; and validates analysis and outcomes.
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Specialized experience for this position must include experience applying design and implementation of data science and analytical methods such as exploratory data analysis, descriptive analytics, and predictive analytics using machine learning.
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Developing and maintaining data analytics models and tools to support ongoing monitoring and reporting of compliance metrics; Providing guidance and training to team members on data analytics techniques and tools.
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