Top Hybrid Data Science Jobs
The role involves leveraging advanced analytics to extract insights from large datasets, leading teams in AI and GenAI solution development, managing project execution, mentoring team members, and ensuring adherence to professional standards. It requires collaboration with clients to identify problems and design effective AI architectures.
As an AI & GenAI Data Scientist, you will leverage advanced analytics techniques to extract insights from large datasets, develop analytical models, and implement AI solutions. Responsibilities include collaborating with clients to address their business problems, designing AI architectures, and managing operations within a global data and analytics team.
As a Senior Associate in AI & GenAI Data Science at PwC, you will leverage advanced analytics techniques to extract insights from large datasets, collaborate with clients to solve complex business problems, and develop AI solutions. Responsibilities include model development, data processing, and managing client relationships while guiding the data analytics team.
The Applied Researcher I at Capital One will collaborate with cross-functional teams to develop AI-powered products. Responsibilities include utilizing a variety of technologies to analyze large data sets, building AI models through their entire lifecycle, and conducting impactful applied research to enhance customer experiences.
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.
Featured Jobs
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.
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.
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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