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Experience with SQL, Python, R, Matlab, Tableau, Alteryx and/or other data analytics tools. Analyze market and stress test risk exposures for all products and accounts cleared by Analysis is performed using proprietary tools/applications; Products include equities, government securities, options, futures options, and futures |Assist in the creation, maintenance, execution and reporting of daily stress testing activities which includes coordinate with IT resources to support the systems development needs of the group.
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Understanding of common market risk methodologies such as VaR, SPAN, stress testing, liquidity risk, and concentration risk, preferred. Develop tools to assist in the preparation of position and financial exposure reporting based on large data set analysis, including the impact of stress test results on Financial and Liquidity Resources.
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Keep current with market conditions to assess the needs to adjust stress test practices in light of changes in market conditions and/or business lines. Sound understanding of market/credit/liquidity risk management and corresponding mitigation factors.
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Ability to create simple-to-understand visualizations of data using Tableau and/or Power BI. The Space Planning Analyst applies advanced analysis to specific planogram/modular and market performance that will drive actionable recommendations for future planning and decision making.
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Provide leading edge Category Management solutions, using and understanding IRI and Nielsen syndicated scanning data, Household Panel, market demographic data, customer point-of-sale, loyalty data, and systems used to produce the information for Category reviews.
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Experience with Looker Data Studio (Google Data Studio) and/or similar tools to build dashboards (Tableau, PowerBi, etc. Reporting to the Global Digital Director, the Sr Digital Manager will closely collaborate with the leaders of integrated marketing communications, customer experience and market and consumer insights.
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As an Associate in our Risk Analytics and Modeling team, you’ll have the opportunity to apply your quantitative, modeling and analytical skills in a real world environment to develop or validate statistical, financial engineering, and AI/machine learning models in the areas of credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics area.
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Technology Utilization - Leverage data management and analytics tools, such as Excel, Domo, SFDC, SQL, Python, R, and Tableau, to streamline data processes and enhance analytical capabilities.
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Proficiency in Python, R, SQL and experience with data visualization tools (Looker, Tableau) Strong analytical mindset and attention to detail Exceptional communication and interpersonal skills, with the ability to work collaboratively and cross-functionally with internal and external stakeholders.
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Proficient in the use of financial market applications (FactSet, Refinitiv Eikon, Bloomberg), database, data intelligence software (e.g. Tableau, Power BI and a power user of Microsoft Office, specifically Excel & PowerPoint.
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Python (Pandas, Numpy)Tableau, Airflow, Looker, Mode, PrefectAdditional InformationBlock takes a market-based approach to pay, and pay may vary depending on your location. Check out our locations, benefits, and more at Job DescriptionThe Data Science team at Cash App derives valuable insights from our extremely unique datasets and turns those insights into actions that improve the experience for our customers every day.
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Aimpoint Digital is a remote-first market leading analytics, decision sciences, data engineering, and AI advisory and solution engineering firm with a global reach and a mission to drive business outcomes for organizations through data.
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Experience with pharmaceutical data sources (e.g., IQVIA or Symphony claims, specialty pharmacy data, and Syndicated data sources); Deep understanding across various pharmaceutical data facets/processes, including data creation and acquisition, management, governance, data quality, integration, visualization and statistical modelling.
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Hands on experience and proficiency with analytical & visualization tools (Python and R preferred; SQL, SAS, Tableau, Qlik, Alteryx, PowerBI, etc.) Collaborate with Global and US Teams to develop new product launch strategy and life cycle management plan in rare disease market.
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Knowledge of tools such as Python, R, SQL, Data Modeling, ETL, JSON, XML, Oracle Dashboards, Tableau, Visual Basic and Microsoft Access. Maintain dashboards to provide a narrative structure and data visualization of Schneider's perspective on the current and future state of the market.
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