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The Senior Data Scientist will conduct research on emerging technologies in AI, develop machine learning models, refine integration patterns for these models, and collaborate with business and product teams to enhance customer experiences and business outcomes.
The Senior Director of Technical Program Management will oversee strategic initiatives in the Enterprise Data and Machine Learning division, optimizing data management and driving innovation through complex technical projects. The role involves aligning cross-functional teams, ensuring successful delivery of data-driven solutions, and fostering a strong TPM discipline within the organization.
As the Senior Director of Technical Program Management at Capital One, you will lead strategic initiatives in the Enterprise Data and Machine Learning division. Responsibilities include overseeing technical project delivery, managing cross-functional teams, and enhancing data management systems. You will leverage your expertise to drive innovative data solutions and develop the TPM practice within the organization.
As a Principal Data Scientist at Capital One, you will lead the use of advanced machine learning and data science methods to drive business outcomes. Responsibilities include building ML models, collaborating with product teams, conducting experiments, and operationalizing solutions in production systems handling large datasets.
As a Senior Manager of Machine Learning Engineering, you'll design and implement machine learning applications while ensuring their performance and availability. You'll collaborate with cross-functional teams to solve business problems using ML, build optimized models, and maintain production systems, all while following best practices in AI development.
As the Applied AI/ML Lead, you will develop and implement production-grade ML models to tackle business challenges in commercial banking, using large-scale data processing frameworks and advanced machine learning techniques. You will build end-to-end ML pipelines and collaborate on modeling experiments.
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The Principal Data Scientist will lead the Data Science function focused on customer retention and growth, developing ML models, guiding a team, and collaborating with various departments to solve business problems using data science and analytics. This role will also involve optimizing ML model performance and enhancing enterprise-wide analysis tools.
The Senior Advanced Analytics Analyst will develop AI models and data visualizations to drive insights, implement global standards for data models and KPIs, and contribute to Sanofi's digital transformation in healthcare.
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As a Staff Machine Learning Engineer, you will lead the design and development of Generative AI solutions for Firefox, focusing on building infrastructure and ensuring model performance and reliability. This role involves collaborating with cross-functional teams and mentoring junior engineers.
The Data Scientist will support data science needs by performing data mining, statistical analysis, and building predictive models for the Cybercrime and Analytics Group. Responsibilities include optimizing classifiers, data processing, anomaly detection, and assisting with IT support as needed.
The Principal Data Engineer will lead the development and implementation of machine learning models for operations, collaborate with team members to enhance product improvements, and optimize data processing pipelines. This role requires strong technical expertise in data analysis, metadata management, ensuring privacy compliance, and mentoring junior engineers.
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As a Data Engineer at StackAdapt, you will design and implement modular and scalable real-time data pipelines, work on custom ML algorithms, and manage microservices for training and monitoring ML models in a collaborative environment.
The Head of Data will shape the data strategy at Gemini, build a high-performance data team, manage data infrastructure, optimize data warehousing, and drive data-driven initiatives across the organization. Responsibilities include overseeing data management, analytics, and collaborating with executive leadership on data integration into business strategies.
The Vice President of Data Science Research will lead the research organization focusing on innovative quantitative methods for liquid biopsy cancer screening, drive the research roadmap, and transition new concepts into product development while maintaining reproducible research standards.
As a Data Scientist at Pinterest, you will utilize quantitative modeling and statistical methods to solve complex engineering challenges. Collaborating with cross-functional teams, you'll develop best practices for experimentation, build analysis pipelines, and provide crucial insights that influence product development.
As a Staff Machine Learning Engineer at Handshake, you will lead a small team to enhance AI products and infrastructure, focusing on Generative AI and Recommendations. You will develop machine learning systems, design partnerships across teams, and drive technical direction while ensuring high-quality execution and user-centered solutions.
The ML Postdoc Researcher will design and develop large language models and generative models in collaboration with engineers and researchers. Responsibilities include training LLMs, staying updated with advancements in the field, and contributing to innovative healthcare solutions.
The Technical Director for Machine Learning Engineering will lead the Advanced Analytics and ML Services team at Epic Games, guiding the technical direction and implementing scalable solutions for real-time and batch workloads, while mentoring Data Scientists and engineers, and collaborating with cross-functional teams.
The AI Solution Manager role involves leading C3 AI teams to deliver AI/ML applications, collaborating with federal agencies to identify use cases, and contributing to product strategy. Responsibilities include project management, technical problem solving, and delivering presentations to senior stakeholders, with frequent travel required.
The Data Scientist will enhance organizational performance through innovative analytics models and processes. Responsibilities include collaborating with business stakeholders to identify opportunities for analytics solutions, conceptualizing and designing models to address business problems, sourcing data with Data Engineers, and fostering data science capabilities within teams.
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As a Graduate Quantitative Researcher, you will develop algorithmic trading strategies using statistical models and machine learning. You will analyze vast data sets, create complex models to predict market movements, and work with a team of experts to drive innovative solutions for trading strategies.
As a Staff Machine Learning Engineer at Path Robotics, you will lead the development of advanced AI systems for robotics, utilizing behavioral cloning and reinforcement learning. Responsibilities include collaborating on control algorithms, integrating with hardware, conducting simulations, and troubleshooting robotic systems to enhance their capabilities.
The System Engineer will integrate AI into wargaming efforts, collaborating with experts to enhance scenarios, develop roadmaps, implement data analysis methods, and create real-time analytics using tools like Power BI. The role includes conducting experiments, ensuring data integrity, and exploring AI applications to streamline processes.
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The Manager of Generative AI Applied ML will lead a team of research and ML engineers to deliver scalable solutions for Scale's Generative AI Data Engine. Responsibilities include integrating machine learning into human-in-the-loop systems, implementing state-of-the-art research into production, and managing large datasets to improve model performance for various applications while ensuring high-quality outputs.
As a Perception Software Engineer at Zipline, you will be responsible for developing and implementing innovative perception systems for autonomous aircraft. This includes selecting sensor configurations, designing algorithms for object perception and avoidance, building software infrastructure to improve algorithms, and collaborating with various teams for effective decision-making processes.
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