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DE performing Asset Liability Management data analysis using SQL Developer and Excel; and developing custom solutions to support trading and investment management, using Business Intelligence tools.
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What you will be responsible forDevelop/ Build and enhance data pipelines using Python, Spark based data engineering solutions (Databricks), and SQL (AWS Redshift). Hands on development in Python, PL/SQL, SQL, Shell Scripting, AutoSys. Hands on experience working in cloud data platforms such as AWS Redshift, Spark based data engineering solutions.
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Have experience with data analysis tools (JMP, Minitab) and data visualization tool (Tableau, Power Bi, SQL, etc.) Have experience with data analysis tools (JMP, Minitab) and data visualization tool (Tableau, Power Bi, SQL, etc.
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Knowledge on technical competence with the latest technologies (Azure, Power BI, SQL Server, SSIS, SSRS, SSAS, Azure/AWS Cloud, Devops (ADO), Snowflake, Mobility & Security) Knowledge with Azure services: Azure Blob Storage, Azure SQL Server, Azure Data Factory.
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Working in R, SQL, Tableau, Stata, SAS and/or Python to create analytic files and conduct analyses using claims, discharge, and survey data. Experience programming with Stata, SAS, SQL, Python and other standard statistical software.
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You have a strong knowledge of Databricks features and functionalities, such as Unity Catalog, Audit Logs, Databricks SQL and Delta Live Tables. You are proficient in at least one primary language (e.g., Java, Scala, Python) and Advanced SQL (any variant.
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Demonstrated experience with at least one of following: Python, R, Tableau, Excel or SQL with structured and non-structured data mart. The Centralized Modeling & Analytics (CMA) team within State Street's Enterprise Risk Management (ERM) organization is looking for an experienced quantitative analyst to join our team in Boston, MA; Stamford, CT OR Clifton, NJ.
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Proficiency in complex data extraction or processing using Python, SQL, Snowflake. We assist companies and non-profit organizations in delivering benefits to their employees. We are seeking a Vice President, Data Science to join the Fidelity Digital Asset Management business and report directly to the Head of Digital Asset Operational Capabilities.
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Knowledge of AI/ML tools, query languages/tools (SQL, Alteryx), blockchain technology and data visualization tools. Play a critical role in setting up in-house chargeback function, working cross-functionally with 3PL, Trade & Distribution, Accounting, and DTE, etc.
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Data bases (SQL, NoSQL) and Data Platforms (Databricks, Snowflake) Strong skills with Database management, Data modeling and design DevOps and Security CI/CD, Serverless compute, OAuth, SSO, MFA etc.
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Experience with core IBM mainframe technologies including but not limited to z/OS, CICS, storage, DB2, z/OSMF, SDSF, JES2, VTAM. ISPF, JCL, VSAM utilities, assembler, RACF, SQL, CLIST, REXX, COBOL, MQ, SMPE, Db2 utilities, mainframe monitors, JCL checker, Unix System Services.
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Expertise with core data science languages (such as Python, R, Scala), and proficiency with key database systems (e.g. SQL, NoSQL). Comfortable working in cloud and high-performance computing environments (e.g. AWS, GCP, Databricks, Apache Spark, Snowflake.
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Extensive experience with the Microsoft Cloud Ecosystem, including the following: SharePoint Online, PowerShell (and usage for BC deployments), Business Central Cloud/SaaS, Microsoft Azure Platform and Services, Azure SQL DB About Sphere.
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Proficiency with SQL, Excel, Tableau (at least two of the three) Experience with audience tools such as SCOUT (Mediahub quantitative surveying), Comscore, MRI, Exact Target; creative/brand evaluation and tracking tools like Kantar Millward Brown, Nielsen Brand Effects, YouGov, Dynata, Survata; search tools like Adwords, Kenshoo; social tools like Crimson Hexagon, Netbase.
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