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JPMorgan Lead Geospatial Data Scientist - CB Distribution Analytics United States, Ohio
Work with partners in Real Estate, Corporate Strategy, Distribution Strategy, Data and Analytics, and various lines of business to understand and document analytic project objectives, deliverables, and timelines. Ensure constant...
Create plans on how to develop and deliver data for their business area to support business operations, strategic objectives, and advanced analytics. Work with key partners across products, processes, and...
Analyze and interpret complex client data to provide insightful recommendations, leveraging your expertise in data analytics. Manage high-touch client relationships, utilizing your advanced customer service skills to address inquiries, troubleshoot...
Directly manages and help develop team members within the OSD team. Manages incoming and outgoing Client queries related to the end-to-end Margin Services function. Proactively monitors and maintains Operational Service...
Oversee the delivery of technology projects, ensuring adherence to methodologies like Agile and Waterfall, and mentoring team members. Drive continuous improvement and innovation, applying research, analysis, and best practices to...
Lead the design and implementation of climate risk data and analytical frameworks to support the bank's risk management strategies, with a focus on understanding and integrating different climate models. Oversee...
Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next. Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful...
Work with partners in Real Estate, Corporate Strategy, Distribution Strategy, Data and Analytics, and various lines of business to understand and document analytic project objectives, deliverables, and timelines. Ensure constant...
Data Scientists are responsible for analyzing and interpreting large and complex datasets to uncover insights that inform business decisions and drive innovation. They use a combination of statistical and machine learning techniques, as well as programming languages such as Python and R, to extract, clean, and transform data. They also use tools such as SQL, Hadoop and Spark to work with large datasets and perform data analysis.
Data Scientists work closely with cross-functional teams, such as product managers, marketing and operations, to understand their specific data needs and provide them with insights to make informed decisions. They also collaborate with data engineers to build and maintain the infrastructure necessary for data analysis. They also use data visualization tools such as Tableau and Power BI to create interactive dashboards and reports to communicate data insights clearly and effectively to non-technical stakeholders.