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In supporting rule analysis, Teammate should be able to Independently perform sophisticated data analytics that fit to the fraud problem being observed (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data.
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Multiple Data and Analytics solutions and tools such as dbt, Alteryx, Collibra, Alation, Fivetran, Matillion, Tableau, PowerBI, etc. Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in analytics, decision science, data engineering and infrastructure.
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Possessing skills in Data Migration and Management, Data Governance, Reporting and Analytics, Planning and Consolidation, Cloud Databases and Advanced Analytics; In joining our data and analytics team, you'll work with our clients to leverage SAP applications to transform their data management and governance and analytics processes by enhancing their core transaction processing and reporting competencies ultimately strengthening their ability to support management decision making and corporate strategy.
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The purpose of the Analyst, Predictive Modeling position is to analyze data to drive better business decisions, including: Pricing and credit risk, loan servicing strategies, business policies, processes, and performance, and champion/challenger tests.
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Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support the development of health policy. Experience working with healthcare claims and enrollment data in large data warehouse environments (e.g., IDR.
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This is a custom analytics, research and consulting team that delivers data-driven strategic marketing insights to our clients. Job Description Razorfish is looking for a Senior Analyst to join its Data Science and Analytics Discipline.
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Own analytics projects end-to-end, working with stakeholders to scope the problem, analyzing the data to get insights, and communicating results. Utilize analytical tools and scripting languages (SAS, SQL, R, Python) to access and analyze data.
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Building these controls requires knowledge of big data techniques, ability to architect systems that can efficiently scale to hundreds of billions of data points per day, machine learning over unstructured and structured data, graph analytics, and experience with building UI for data rich applications.
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Due to the unique complexities of the business such as technology and data security, it is time for a new partner with the appropriate expertise and resources to invest in the future growth of Kodiak.
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Work with complex data structures; cleanse data and perform statistical analyses such as: marketing mix modes (MMM), digital multi-touch attribution (MTA), TV attribution, media response analysis, time series analysis, predictive modeling, cluster analysis, user overlap analysis, path to conversion analysis, website analytics, lifetime value (LV) analysis, discrete choice/conjoint analysis, latent class & other clustering techniques (segmentations), multivariate & logistic regressions (ex.
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Exposure Data Modeling using Star/Snowflake Schema Design, Data Marts, Relational and Dimensional Data Modeling, Slowly Changing Dimensions, Fact and Dimensional tables, Physical and Logical data modeling Produce client deliverables such as detailed design documentation, configuration documentation, unit test plans, and training curriculum Required Qualifications: A bachelor's degree in Computer Science or a related field.
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But successful members of the Analytics team at Zenith generally have a passion for emerging tech and media, bring a data-driven approach to decision-making, have a fresh perspective and share it in a positive way, don’t shy away from a challenge, and are always hungry to learn more.
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Familiarity with Industry 4.0 concepts such as, IoT, Edge, Data Hub, predictive maintenance, Digital thread, control tower and others. You know data acquisition, distribution, processing and visualization technologies used in the manufacturing domain (sensors, IoT, data platforms, dashboarding and BI tools.
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Experience as a hands-on contributor or in leading a team to develop multiple advanced analytics solutions or design/implement large data engineering programs in areas such as price optimization, underwriting risk management, market mix effectiveness analysis agency management, customer lifetime value, customer segmentation, claims analytics, contact centre analytics, etc.
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Advanced degree (master's or PhD) in Statistics, Machine Learning, Computer Science, Engineering, Data Analytics etc. Experience in model development cycle end to end in the enterprise environment including business problem scoping, data ingestion, feature engineering, developing machine learning models and performing validation of model performance.
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data job Title: analytics in Atlanta, DE, Germany
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