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Develop and implement data science and machine learning models to enhance educational platforms and personalized learning experiences. Create data visualizations and optimize ETL processes to provide actionable insights for educational stakeholders.
You will define and deliver the strategic vision for Data Science and AI across the Marketing, Sales, and Customers organization to drive business value. You will lead the development and deployment of AI solutions while establishing frameworks for responsible AI and ethical decision-making.
The co-op will support the product team by working on new product features and conducting rigorous data analysis. You will collaborate across functions and communicate findings to non-technical stakeholders.
Lead the design and end-to-end delivery of complex machine learning, artificial intelligence, and advanced analytics solutions, establishing standards that support scalable, high-quality production systems. Provide technical direction and mentorship, partner with business and technical stakeholders, and communicate findings and recommendations to guide strategic decisions.
Modify and optimize SQL queries, use business intelligence tools to visualize data and identify insights, and design and analyze enhancements. Participate in discussions, coding, and testing, and document coding changes.
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Lead a team of data engineers and scientists to build and scale AI systems for content moderation, customer support, and business operations. Balance hands-on coding and model development with strategic team management and cross-departmental collaboration.
You will lead a team of data engineers and scientists to build and scale AI systems for content moderation, customer support, and business operations. This is a player-coach role where you will spend half your time managing the team and the other half writing code and debugging production systems.
Lead a team of data engineers and scientists to build and maintain AI-driven moderation and customer support systems. Balance hands-on coding and model development with strategic team leadership and cross-departmental collaboration.
The role involves leading end-to-end data science projects and developing advanced machine learning models to solve complex business and clinical problems. You will also serve as a primary subject-matter expert, providing technical guidance to the team and translating analytical findings into strategic recommendations for leadership.
The Programme Director will provide technical leadership, management, and strategic direction for the Data Science and GIS Employment Accelerator. They are responsible for achieving programme training and employment targets while overseeing resource allocation and stakeholder engagement.
Provides technical leadership for data science and AI/ML workstreams supporting U.S. Army enterprise data modernization. Formulates and delivers AI/ML-based decision-making models while managing technical roadmaps and stakeholder communications.
Partner with cross-functional teams of data scientists, engineers, and product managers to deliver intelligent, data-driven products. Build and implement machine learning models across all phases of development to solve complex business problems.
You will work with a team of data scientists and AI engineers to develop, train, and deploy ML models and AI agents. Additionally, you will communicate with stakeholders to understand business processes and support high-visibility AI projects.
The Data Science Lead will design, operationalize, and scale advanced analytics, machine learning, and AI solutions to support Risk Consulting engagements. They will also build robust data pipelines, develop reusable analytics assets, and mentor junior team members on best practices.
You will act as a trusted advisor to enterprise customers, designing scalable AI architectures and driving the adoption of NVIDIA's generative AI platforms. This involves leading technical engagements, conducting proof-of-concept demonstrations, and collaborating with internal engineering and product teams to deliver full-stack AI solutions.
The Data Science Manager will lead a team in the end-to-end delivery of production-ready data science systems, including data engineering and model deployment. They are responsible for setting technical direction, mentoring direct reports, and partnering with stakeholders to align data initiatives with business goals.
The intern will define and implement evaluation frameworks for agentic AI harnesses and analyze telemetry data to drive model performance improvements. They will also contribute to building an internal AI governance pipeline and document methodologies for harness tuning.
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The Senior Manager will lead real-world evidence strategies and data science workstreams to support Immunology research and development programs. They will collaborate with cross-functional teams to translate therapeutic priorities into actionable research questions and provide technical expertise for clinical decision-making.
Architect and deliver complex statistical, machine learning, and generative AI initiatives to solve high-impact clinical and business problems. Lead technical direction, mentor junior data scientists, and partner with clinical leaders to ensure model safety and validation.
The Director will lead the development and scaling of advanced analytics and AI-enabled solutions to support decision-making across Commercial, Medical Affairs, and Clinical Operations. This role involves partnering with cross-functional teams to translate complex data into actionable insights while championing responsible AI practices and data governance.
The Director of Product Management, Data Science defines and executes the product strategy and roadmap for a portfolio of data science products. This role leads product managers and collaborates with cross-functional teams to ensure data science solutions are scalable, production-ready, and deliver measurable business value.
You will lead a team of scientists and engineers to design AI/ML models and define long-term strategy for agentic AI products. This involves influencing senior leadership, driving business value at scale, and overseeing the development of benchmark models to ensure system integrity.
The Data Science Manager will lead strategic analytical initiatives and develop machine learning models to improve customer experiences. They will partner with cross-functional teams to translate complex data insights into tangible business goals and digital products.
Analyze course performance metrics and student feedback to identify and implement necessary content updates. Maintain and troubleshoot technical learning environments, including Docker-based workspaces and cloud-based labs on AWS and Azure.
The Principal Forward Deployed Engineer will serve as a primary technical leader for strategic accounts, driving business outcomes through hands-on execution. They will build and ship production-grade solutions while collaborating directly with customers to translate business needs into technical approaches.
The Lead AI Engineer will design, build, and deploy production-grade AI and machine learning algorithms to support enterprise and government programs. This role involves mentoring staff, translating complex technical requirements into actionable solutions, and maintaining high-quality software standards.
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The Director will build and lead the bioinformatics function, defining strategy and vision for genomic algorithm development. They will also architect scalable AWS infrastructure and implement MLOps to ensure reliable deployment of clinical products.
Lead the design and deployment of ML-driven underwriting strategies and credit risk frameworks to optimize portfolio performance. Manage a team of data scientists and risk analysts while partnering with cross-functional departments to drive business growth and financial access.
Lead the research and development of data products and predictive models to drive insights for small business credit and risk management. Collaborate with product, engineering, and revenue teams to commercialize analytical tools and serve as a subject matter expert for clients.
You will translate business problems into analytical work and explore data to build AI-driven solutions. Additionally, you will design experiments to measure performance and collaborate with engineers to deliver client solutions.
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