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Education: Advanced degree or equivalent experience in Statistics, Econometrics, Operations Research, Actuarial Science, Applied Mathematics, or other applied quantitative science, or equivalent education and related training.
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Actuarial Science, Business Administration/Management, Commerce, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Economics, Engineering, Engineering and Business, Finance, Information Technology, Management Information Systems, Mathematics, Mechanical Engineering, Operations Management/Research, Risk Management, Software App, Statistics.
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Coordinate with other Front Line Units and Control Functions (FLU/CFs) Data Strategy and Management teams to streamline the Data Sourcing Strategy for Risk Organization. This job is responsible for defining Data Architecture strategy for Global Risk Management Organization.
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We are looking to hire a staff machine learning engineer to join our RVO Health data science team. 6+ yrs of professional experience in a data science role with a preference for holding an MS or PhD in STEM with a focus in ML, statistical modeling, or optimization.
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Support City National Bank Group Risk Management (GRM) second line of defense by providing solutions on reporting and data risk needs. Minimum7 years of experience with SAS or SQL, or other data management, reporting and query tools (SharePoint, SAP, Business Objects, Tableau, Crystal reports/Dashboard, etc.
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Supports model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite. Successful candidates will have a Masters or PhD in Math, Economics, Statistics, or similar discipline, and a minimum 2 years relevant experience in statistics, data science, econometrics, and other quantitative analysis.
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BS/BA in Statistics, Mathematics, Operations Research, Management Science, Computer Science, or a related technical field, OR BS/BA in Criminal Justice, Economics, Business, or a related business field.
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The Risk Data Scientist will use analytical skills to identify and prevent fraud & credit risks. You will own the key metrics, develop data pipelines, ETL. You will also make a direct impact on Square's priorities and Banking initiatives (primarily SQ’s debit card) by building risk detection strategies, developing & tracking key success metrics, influencing partners through data and enabling growth of the business.
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Play a leading role in developing, drafting and presenting the comprehensive annual Interest Rate Risk / Liquidity Risk Oversight report which documents MLRM's ongoing review and assessment of Truist's interest rate and liquidity risk management practices and risk position.
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CES creates physical solutions that enhance our natural and structural environments, through a comprehensive understanding of engineering design, landscape architecture and applied science, with the in-house support of geomatics, subsurface utility and construction administration professionals.
$68,000 - $100,000 a yearFull-timeExpandApply NowActive JobUpdated 28 days ago - UpvoteDownvoteShare Job
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Support and administer the Governance Risk and Compliance (GRC) Tool surrouding data mapping, cookie consent, privacy consent, third pary risk management and overall risk management.
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As the Litigation Specialist, you will maintain a case for each matter, complete initial intake, document status of the litigated issue, assess risk, work closely with inside and outside counsel in an attempt to resolve each matter, and organize supplementing data and information to support servicing litigation.
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Design and develop security policies, standards and procedures across various domains (e.g., Resilience, Data Security, IT Asset Management Governance, Digital Trust, IAM, Cloud Security, Application Security, etc.
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Expert level credit analysis skills and experience to evaluate business unit underwriting and portfolio management processes, loan structure, borrower financial condition, repayment capacity, collateral, exceptions, risk rating, key credit risk drivers, and credit review principles and methodologies.
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Conduct data management maturity assessments and identify pain points for including data quality, governance, architecture, analytics, metadata management, master data management.
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