Top Hybrid Data Science Jobs
As a Data Scientist Associate, you will collaborate with various teams to gather requirements and work on analytics related to Chase's branch and ATM distribution network. Responsibilities include developing algorithms for large geospatial datasets, implementing ML models, and documenting analytics processes to meet control obligations.
As a Senior Associate Data Scientist, you will analyze data to support Business Banking strategy, develop data-driven solutions, and ensure data quality for decision-making. Responsibilities include statistical analysis, data processing using Python and SQL, and maintaining data integrity within various project phases.
The AI Model Risk position at MetLife involves managing risks related to Artificial Intelligence and Machine Learning models. Responsibilities include challenging modeling decisions, assessing risks, collaborating with internal teams and vendors, and ensuring mathematical and conceptual soundness of models. Required skills include experience in statistical, ML or AI model development, programming skills in Python, R, and/or C#, and the ability to work collaboratively. A graduate degree in a quantitative field and 3+ years of experience are also required.
As an Associate Director of Data Science, you will develop and implement algorithms to solve complex supply chain issues, use machine learning and operations research, and collaborate with various supply chain functions to optimize operations. You will drive strategic planning initiatives and lead analytics teams for continual improvement in processes and metrics.
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As a Principal Engineer in ML/AI, you will lead technical efforts across teams, drive product development, set engineering standards, and provide mentorship while collaborating closely with various stakeholders to enhance and innovate financial services.
The Principal Engineer will lead efforts in machine learning and AI, collaborating with teams to build impactful products, setting technical standards, and mentoring others. Responsibilities include hands-on development, technical leadership, and influencing hiring and coding practices.
As a Principal Applied Scientist, you will lead the delivery of AI products, collaborate with ML engineers, improve data quality and usability, and engage in public-facing content to enhance Xero's profile. The role requires a focus on creating impactful, customer-facing ML and AI solutions while emphasizing high-quality code from the outset.
As a Senior Research Scientist at Kensho, you will develop innovative solutions in Machine Learning and NLP, focusing on complex tasks like long-context QA and document extraction. Collaborate with a team to enhance existing models, create evaluation benchmarks, and engage in academic partnerships, all while utilizing advanced computational resources.
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The Senior Data Scientist will drive collaboration across teams to analyze data for fraud risks, build machine learning models, and provide insights for risk mitigation. Responsibilities include data refinement, project prioritization, mentoring, and establishing best practices in data science.
The Staff Decision Scientist will lead analytics solutions and provide actionable insights for clients. Responsibilities include optimizing client success, presenting analytical results, leading complex projects, and mentoring others. The role requires a focus on data-driven insights, communication with clients, and participation in analytics community efforts.
As a Revenue Systems Analyst, you will support Revenue Systems and subscription management, ensuring accurate billing operations and revenue recognition. You'll collaborate with various teams, manage the subscription lifecycle, implement automation to enhance efficiency, and provide insights through revenue reports while ensuring compliance with accounting standards.
The Staff Scientist in Biostatistics will provide strategic input for product pre-launch and post-launch activities, including developing statistical analysis plans, conducting clinical and real-world evidence studies, and reporting findings. The role involves collaboration with cross-functional teams and leading future studies related to claims databases and electronic health records.
The Revenue Operations Analyst optimizes revenue processes and performance by managing the revenue forecasting tool, analyzing sales data, and reporting performance metrics. This role involves enhancing sales operations through data-driven insights and collaborating with sales teams to improve forecasting accuracy and sales processes.
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