Top Data & Analytics Jobs
As a Principal Machine Learning Engineer, you will drive the technical roadmap of Snap's Ad Marketplace and Pacing teams, design and scale machine learning models for optimal ad delivery, and collaborate with cross-functional teams. You will stay updated on the latest in machine learning to solve complex problems, advocate for best practices, and provide technical direction to influence the ML community.
The Lead Machine Learning Engineer will focus on developing and optimizing algorithms for Hulu's recommendation and personalization systems. Responsibilities include collaborating with product and data teams, maintaining existing models, and establishing best practices in algorithm development and deployment.
The Staff Machine Learning Engineer will enhance batch inference services and tooling for financial crime detection, work on infrastructure for model development, and lead AI/ML initiatives within Cash App. Responsibilities include collaborating with various teams, developing prototypes, and driving strategic roadmaps.
The Senior Machine Learning Engineer will design and build services for ML modelers, integrate data streams to create efficient models, and lead MLOps initiatives. The role involves collaborating with various teams to enhance ML tools and infrastructure while maintaining production software and developing new solutions.
The Director of Machine Learning Operations will lead the ML Ops team to develop, implement, and oversee machine learning strategies. Responsibilities include managing ML infrastructure, deploying models, ensuring performance and scalability, and collaborating with cross-functional teams to integrate ML solutions into the advertising technology platform.
The Machine Learning Engineer will focus on enhancing search relevance and personalization on Instacart's platform by developing and optimizing machine learning models. Collaboration with cross-functional teams is vital to create scalable solutions while also contributing to research and thought leadership.
As a Machine Learning Engineer at Kalepa, you will lead the development and deployment of machine learning models to gauge business risks, utilizing diverse data sources. You'll have full project ownership and collaborate closely with Product Management and Software Engineering teams in an agile environment.
As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to analyze risk across various business classes, utilizing extensive structured and unstructured data. You will work closely with Product Management and Software Engineers within an agile environment to drive project ownership and direction.
Featured Jobs
As a Senior Machine Learning Engineer, you'll lead the development and deployment of machine learning models to analyze business risks. You'll handle structured and unstructured data to derive insights and work closely with product and software teams while managing your project ownership.
As a Machine Learning Engineer at Kalepa, you will lead the development and deployment of machine learning models to assess risk across various business classes. You will convert large volumes of structured and unstructured data into actionable insights, working closely with Product Management and Software Engineers over two-week sprints.
As a Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess the risk of various businesses by analyzing structured and unstructured data from multiple sources, including web data and satellite imaging.
The Machine Learning Engineer will lead the development and deployment of machine learning models to assess the risk of various business classes. Responsibilities include analyzing structured and unstructured data to derive insights and ensuring project ownership and direction within a two-week sprint cycle.
As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models to assess business risk, utilizing both structured and unstructured data. You will work closely with Product Management and Software Engineers in an agile environment, taking ownership of your projects to drive their direction and execution.
The Senior Machine Learning Engineer at Kalepa will lead the development and deployment of machine learning models to assess business risk using structured and unstructured data. Responsibilities include project ownership, collaboration with product managers and software engineers, and working within a two-week sprint cycle.
The Senior Machine Learning Engineer will lead the development and deployment of machine learning models to analyze business risks. This role requires turning large volumes of structured and unstructured data into actionable insights while managing project direction and collaborating with teams on a two-week sprint cycle.
As a Principal Data Scientist at Zocdoc, you will lead the Search team to enhance their Provider Recommendation System using machine learning algorithms. You will analyze data, interpret results, collaborate with various business partners, and mentor junior data scientists to drive strategic data initiatives in healthcare.
The Senior Machine Learning Engineer will lead the development and deployment of machine learning models to assess business risks. Responsibilities include working with large datasets, collaborating with product management and software engineers, and guiding projects through a two-week sprint cycle.
The Machine Learning Engineering Specialist at ZS will design and implement ML features, collaborate with client teams, write production-ready code, ensure deliverable quality, conduct testing, participate in agile ceremonies, evaluate new technologies, and support project architecture.
The Senior Staff Data Scientist will work closely with the Marketing team to enhance marketing initiatives through statistical modeling and machine learning. Responsibilities include implementing Media Mix Models, conducting performance analysis, building attribution models, and developing dashboards to communicate insights. Staying updated with industry trends and technologies is also crucial.
The Senior Data Scientist in Marketing Analytics will collaborate with the Marketing team to enhance the ROI of marketing initiatives through statistical modeling, machine learning, and data mining. Responsibilities include leading Media Mix Models, establishing marketing measurement frameworks, performing in-depth marketing performance analyses, and developing dashboards to communicate insights.
The Data Scientist will contribute to innovative projects in data science, machine learning, and AI across various sectors, engaging with military and civilian customers to apply cutting-edge technologies and algorithms. They will collaborate with diverse teams, mentor peers, and focus on developing frameworks and tools for mission-critical applications.
As a Machine Learning Engineer at ZS, you'll build and monitor model pipelines, scale algorithms for large datasets, implement ML Ops, write production-ready code, and collaborate with teams to deliver AI-enabled solutions in healthcare. You'll also research new technologies and contribute to the enhancement of ML engineering platforms.
The Senior Scientist will advance Tempus' drug R&D platform by performing complex analyses, developing algorithms for precision medicine, and collaborating with Research, Engineering, and Data Science teams. Responsibilities include driving innovation, co-developing solutions with clients, and effectively communicating insights from extensive multimodal datasets to diverse stakeholders.
As a Senior Machine Learning Engineer at Kalepa, you will lead the development and deployment of machine learning models to analyze business risks using diverse data sets. You will collaborate closely with Product Management and Software Engineers while driving project focus in a fast-paced environment.
As a Senior Machine Learning Engineer at Rokt, you will design and build machine learning models to tackle various business challenges, work on user targeting, segmentation, and dynamic ad content generation, and mentor team members while collaborating closely with cross-functional teams.
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