Top Data & Analytics Jobs in NYC, NY
Create tools to assess organizational health, diagnose business needs, and analyze data for people strategy. Partner with stakeholders to design Tableau dashboards, translate complex issues into insights, and drive data integrity.
Seeking a Staff Pricing Analyst to develop and optimize pricing strategies, leverage pricing models for profitability, and present analyses to business leaders. Requires a B.S. or M.S. in a quantitative field, 7+ years of industrial experience in pricing or financial services, exceptional programming skills in SQL and Python, and strong knowledge of Tableau.
The Senior SOX IT Tester & Data Analyst is responsible for executing IT control testing and assessments, ensuring compliance with SOX requirements, and working closely with IT teams to maintain control documentation and address deficiencies. The role involves data analytics and reporting to the SOX Steering Committee on control status and remediation efforts.
The Staff Data Scientist will be responsible for developing loss forecasting models for various lending products, analyzing large datasets, and collaborating with multiple teams to provide insights into losses. They will need advanced analytical and technical skills in data analysis and modeling using Python and other statistical packages.
As a Risk Data Analytics Manager, collaborate with senior leadership to provide data-driven insights and support risk oversight using innovative data visualizations. Conduct quantitative analysis, prepare risk reports, and maintain datasets for risk analytics.
As a Risk Data Analytics, Senior Manager, you will be responsible for developing analytics tools and solutions to drive data-driven decision making in the financial services industry. You will collaborate with senior leadership to identify opportunities, develop cutting-edge analytical solutions, and deliver actionable insights for risk oversight strategies.
Seeking an experienced Senior Staff Data Scientist to lead machine learning efforts, develop and deploy ML models to improve product experience, and work closely with Product and Engineering teams.
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